TP : Analyse de sentiments dans les critiques de films

Objectifs

1. Représenter des données textuelles de manière simple.
2. Utiliser un modèle d'apprentissage statistique basique pour une tâche d'analyse de sentiments.
3. Tenter d'améliorer ces représentations avec des outils venus du traitement automatique du langage
4. Comparer les résultats avec une méthode coûteuse état-de-l'art: fine-tuner un modèle Bert.

Dépendances nécessaires

Pour les objectifs 2. et 3., on aura besoin des packages suivants:

• The Machine Learning API Scikit-learn : http://scikit-learn.org/stable/install.html
• The Natural Language Toolkit : http://www.nltk.org/install.html

Les deux sont disponibles avec Anaconda: https://anaconda.org/anaconda/nltk et https://anaconda.org/anaconda/scikit-learn

Pour l'objectif 4., il faudra installer le package transformers: https://huggingface.co/transformers/index.html

import os.path as op
import re 
import numpy as np
import matplotlib.pyplot as plt
import gdown

!pip install transformers

Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/
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gdown.download("http://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz", output="aclImdb_v1.tar.gz", quiet=False)
!tar xzf /content/aclImdb_v1.tar.gz

Downloading...
From: http://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz
To: /content/aclImdb_v1.tar.gz
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Charger les données

On récupère les données textuelles dans la variable train_texts;

On récupère les labels dans la variable $train_labels$: $0$ indique que la critique correspondante est négative tandis que $1$ qu'elle est positive.

from glob import glob
# We get the files from the path: ./data/imdb1/neg for negative reviews, and ./data/imdb1/pos for positive reviews
train_filenames_neg = sorted(glob(op.join('.', 'aclImdb', 'train', 'neg', '*.txt')))
train_filenames_pos = sorted(glob(op.join('.', 'aclImdb', 'train', 'pos', '*.txt')))

"""
test_filenames_neg = sorted(glob(op.join('.', 'aclImdb', 'test', 'neg', '*.txt')))
test_filenames_pos = sorted(glob(op.join('.', 'aclImdb', 'test', 'pos', '*.txt')))
"""

# Each files contains a review that consists in one line of text: we put this string in two lists, that we concatenate
train_texts_neg = [open(f, encoding="utf8").read() for f in train_filenames_neg]
train_texts_pos = [open(f, encoding="utf8").read() for f in train_filenames_pos]
train_texts = train_texts_neg + train_texts_pos

"""
test_texts_neg = [open(f, encoding="utf8").read() for f in test_filenames_neg]
test_texts_pos = [open(f, encoding="utf8").read() for f in test_filenames_pos]
test_texts = test_texts_neg + test_texts_pos
"""

# The first half of the elements of the list are string of negative reviews, and the second half positive ones
# We create the labels, as an array of [1,len(texts)], filled with 1, and change the first half to 0
train_labels = np.ones(len(train_texts), dtype=np.int)
train_labels[:len(train_texts_neg)] = 0.

"""
test_labels = np.ones(len(test_texts), dtype=np.int)
test_labels[:len(test_texts_neg)] = 0.
"""

/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:24: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations

'\ntest_labels = np.ones(len(test_texts), dtype=np.int)\ntest_labels[:len(test_texts_neg)] = 0.\n'

Exemple de document:

open("./aclImdb/train/neg/0_3.txt", encoding="utf8").read()

"Story of a man who has unnatural feelings for a pig. Starts out with a opening scene that is a terrific example of absurd comedy. A formal orchestra audience is turned into an insane, violent mob by the crazy chantings of it's singers. Unfortunately it stays absurd the WHOLE time with no general narrative eventually making it just too off putting. Even those from the era should be turned off. The cryptic dialogue would make Shakespeare seem easy to a third grader. On a technical level it's better than you might think with some good cinematography by future great Vilmos Zsigmond. Future stars Sally Kirkland and Frederic Forrest can be seen briefly."

Dans tout ce TP, l'impact de vos choix sur les résultats dépendra grandement de la quantité de données utilisée: essayez de faire varier le paramètre k dans l'encart suivant !

# This number of documents may be high for most computers: we can select a fraction of them (here, one in k)
# Use an even number to keep the same number of positive and negative reviews
k = 2
train_texts_reduced = train_texts[0::k]
train_labels_reduced = train_labels[0::k]

print('Nombre de documents:', len(train_texts_reduced))

Nombre de documents: 12500

On peut utiliser une fonction utilitaire de sklearn, train_test_split, pour la séparation des données en ensembles d'entraînement et de validation:

from sklearn.model_selection import train_test_split

train_texts_splt, val_texts, train_labels_splt, val_labels = train_test_split(train_texts_reduced, train_labels_reduced, test_size=.2)

Représentation adaptée des documents

Notre modèle, comme la plupart des modèles appliqués aux données textuelles, utilise les comptes d'occurences de mots dans un document. Ainsi, une manière très pratique de représenter un document est d'utiliser un vecteur "Bag-of-Words" (BoW), contenant les comptes de chaque mot (indifférement de leur ordre d'apparition) dans le document.

Si on considère l'ensemble de tous les mots apparaissant dans nos $T$ documents d'apprentissage, que l'on note $V$ (Vocabulaire), on peut créer un index, qui est une bijection associant à chaque mot $w$ un entier, qui sera sa position dans $V$.

Ainsi, pour un document extrait d'un ensemble de documents contenant $|V|$ mots différents, une représentation BoW sera un vecteur de taille $|V|$, dont la valeur à l'indice d'un mot $w$ sera son nombre d'occurences dans le document.

On peut utiliser la classe CountVectorizer de scikit-learn pour obtenir de telles représentations:

from sklearn.feature_extraction.text import CountVectorizer

Exemple d'utilisation:

corpus = ['I walked down down the boulevard',
          'I walked down the avenue',
          'I ran down the boulevard',
          'I walk down the city',
          'I walk down the the avenue']
vectorizer = CountVectorizer()

Bow = vectorizer.fit_transform(corpus)

print(vectorizer.get_feature_names())
Bow.toarray()

['avenue', 'boulevard', 'city', 'down', 'ran', 'the', 'walk', 'walked']

/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function get_feature_names is deprecated; get_feature_names is deprecated in 1.0 and will be removed in 1.2. Please use get_feature_names_out instead.
  warnings.warn(msg, category=FutureWarning)

array([[0, 1, 0, 2, 0, 1, 0, 1],
       [1, 0, 0, 1, 0, 1, 0, 1],
       [0, 1, 0, 1, 1, 1, 0, 0],
       [0, 0, 1, 1, 0, 1, 1, 0],
       [1, 0, 0, 1, 0, 2, 1, 0]])

Attention: vérifiez la mémoire que les représentations vont occuper (étant donné la façon dont elles sont construites). Quel argument de CountVectorizer permet d'éviter le problème ?

Pour gérer le problème de mémoire il est nécéssaire de diminuer la taille du vocabulaire.

Pour ce faire 2 arguments peuvent être utilisés:

• max_features qui garde ajoute dans le vocabulaire les N mots les plus fréquents.

• min_df qui ignore les mots dont la fréquence de document est strictement inférieure au seuil donné.

Pour gérer le problème de mémoire, j'ai décidé d'utiliser le paramètre max_features que j'ai fixé à 10 000. Cela signifie que les 10 000 premiers mots pour lesquels la fréquence d'apparition est la plus élevée sont sélectionnés

# Create and fit the vectorizer to the training data
vectorizer_train_splt = CountVectorizer(max_features=10000)
bow_train_splt = vectorizer_train_splt.fit_transform(train_texts_splt)
train_splt_features_names = vectorizer_train_splt.get_feature_names()

print("\n\nTrain reduced features names")
print(train_splt_features_names)

print("\n\nVocabulary")
print(vectorizer_train_splt.vocabulary_)

bow_train_splt = bow_train_splt.toarray()
print("\n\nBoW train dimension")
print(bow_train_splt)

/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function get_feature_names is deprecated; get_feature_names is deprecated in 1.0 and will be removed in 1.2. Please use get_feature_names_out instead.
  warnings.warn(msg, category=FutureWarning)

Train reduced features names
['00', '000', '01', '10', '100', '1000', '11', '12', '13', '13th', '14', '15', '150', '16', '17', '18', '18th', '19', '1920s', '1930', '1930s', '1931', '1932', '1933', '1934', '1935', '1936', '1937', '1938', '1939', '1940', '1940s', '1941', '1942', '1943', '1944', '1945', '1946', '1948', '1949', '1950', '1950s', '1951', '1953', '1955', '1957', '1959', '1960', '1960s', '1963', '1964', '1965', '1966', '1967', '1968', '1969', '1970', '1970s', '1971', '1972', '1973', '1974', '1975', '1976', '1977', '1978', '1979', '1980', '1980s', '1981', '1982', '1983', '1984', '1985', '1986', '1987', '1988', '1989', '1990', '1990s', '1991', '1992', '1993', '1994', '1995', '1996', '1997', '1998', '1999', '19th', '1st', '20', '200', '2000', '2001', '2002', '2003', '2004', '2005', '2006', '2007', '2008', '2009', '20s', '20th', '21', '21st', '22', '23', '24', '25', '250', '26', '27', '28', '2nd', '30', '300', '3000', '30s', '33', '35', '3d', '3rd', '40', '40s', '45', '4th', '50', '500', '50s', '5th', '60', '60s', '64', '666', '70', '700', '70s', '73', '75', '80', '80s', '85', '90', '90s', '95', '98', '99', 'aaron', 'abandon', 'abandoned', 'abbott', 'abc', 'abigail', 'abilities', 'ability', 'able', 'ably', 'aboard', 'abomination', 'abortion', 'abound', 'about', 'above', 'abraham', 'abroad', 'abrupt', 'abruptly', 'absence', 'absent', 'absolute', 'absolutely', 'absorbed', 'absorbing', 'abstract', 'absurd', 'absurdity', 'abu', 'abundance', 'abuse', 'abused', 'abusive', 'abysmal', 'academy', 'accent', 'accents', 'accept', 'acceptable', 'acceptance', 'accepted', 'accepting', 'accepts', 'access', 'accessible', 'accident', 'accidental', 'accidentally', 'acclaim', 'acclaimed', 'accompanied', 'accompany', 'accompanying', 'accomplish', 'accomplished', 'accomplishment', 'according', 'account', 'accounts', 'accuracy', 'accurate', 'accurately', 'accused', 'accustomed', 'ace', 'achieve', 'achieved', 'achievement', 'achievements', 'achieves', 'achieving', 'achilles', 'acid', 'acknowledge', 'acquaintance', 'acquire', 'acquired', 'across', 'act', 'acted', 'acting', 'action', 'actions', 'active', 'activities', 'activity', 'actor', 'actors', 'actress', 'actresses', 'acts', 'actual', 'actuality', 'actually', 'ad', 'ada', 'adam', 'adams', 'adapt', 'adaptation', 'adaptations', 'adapted', 'adaption', 'add', 'added', 'addict', 'addicted', 'addiction', 'adding', 'addition', 'additional', 'additionally', 'address', 'addressing', 'adds', 'adequate', 'adequately', 'aditya', 'administration', 'admirable', 'admirably', 'admiration', 'admire', 'admired', 'admirer', 'admission', 'admit', 'admits', 'admitted', 'admittedly', 'adolescent', 'adopted', 'adorable', 'adore', 'adored', 'adrian', 'ads', 'adult', 'adultery', 'adults', 'advance', 'advanced', 'advances', 'advantage', 'adventure', 'adventures', 'adventurous', 'adversity', 'advertised', 'advertising', 'advice', 'advise', 'advised', 'ae', 'aesthetic', 'affair', 'affairs', 'affect', 'affected', 'affecting', 'affection', 'affections', 'affects', 'affleck', 'afford', 'afghanistan', 'afi', 'aforementioned', 'afraid', 'africa', 'african', 'after', 'afterlife', 'aftermath', 'afternoon', 'afterward', 'afterwards', 'again', 'against', 'age', 'aged', 'agency', 'agenda', 'agent', 'agents', 'ages', 'aggressive', 'aging', 'ago', 'agony', 'agree', 'agreed', 'agrees', 'ah', 'ahead', 'ahem', 'ahmad', 'aid', 'aided', 'aids', 'aiello', 'aim', 'aime', 'aimed', 'aiming', 'aims', 'ain', 'air', 'aircraft', 'aired', 'airing', 'airplane', 'airport', 'ajay', 'aka', 'akin', 'akira', 'akshay', 'al', 'ala', 'alain', 'alan', 'alarm', 'alas', 'alba', 'albeit', 'albert', 'album', 'albums', 'alcohol', 'alcoholic', 'alcoholism', 'alec', 'alert', 'alex', 'alexander', 'alexandra', 'alexandre', 'alfred', 'ali', 'alice', 'alicia', 'alien', 'alienate', 'aliens', 'alike', 'alison', 'alive', 'all', 'allan', 'alleged', 'allegedly', 'allegorical', 'allegory', 'allen', 'alley', 'alliance', 'alligator', 'allow', 'allowed', 'allowing', 'allows', 'allusions', 'ally', 'almighty', 'almost', 'alone', 'along', 'alongside', 'alot', 'already', 'alright', 'also', 'alter', 'altered', 'alternate', 'alternately', 'alternative', 'although', 'altman', 'altogether', 'alvin', 'always', 'am', 'amanda', 'amateur', 'amateurish', 'amazed', 'amazing', 'amazingly', 'amazon', 'amber', 'ambiance', 'ambiguity', 'ambiguous', 'ambition', 'ambitions', 'ambitious', 'america', 'american', 'americans', 'amid', 'amidst', 'amin', 'amitabh', 'amok', 'among', 'amongst', 'amount', 'amounts', 'ample', 'amrita', 'amuse', 'amused', 'amusement', 'amusing', 'amy', 'an', 'anakin', 'analysis', 'analyze', 'anchor', 'anchors', 'ancient', 'and', 'anders', 'anderson', 'andre', 'andrei', 'andrew', 'andrews', 'andy', 'ang', 'angel', 'angela', 'angeles', 'angelina', 'angelo', 'angels', 'anger', 'angie', 'angle', 'angles', 'angry', 'angst', 'anguish', 'anil', 'animal', 'animals', 'animated', 'animation', 'animations', 'animator', 'animators', 'anime', 'aniston', 'anita', 'ann', 'anna', 'anne', 'annie', 'anniversary', 'announced', 'annoy', 'annoyance', 'annoyed', 'annoying', 'annoyingly', 'annoys', 'anonymous', 'another', 'answer', 'answered', 'answering', 'answers', 'antagonist', 'anthology', 'anthony', 'anti', 'antichrist', 'anticipated', 'anticipation', 'antics', 'anton', 'antonio', 'antonioni', 'ants', 'antwerp', 'antwone', 'anxiety', 'anxious', 'any', 'anybody', 'anyhow', 'anymore', 'anyone', 'anything', 'anytime', 'anyway', 'anyways', 'anywhere', 'apart', 'apartheid', 'apartment', 'apartments', 'ape', 'apes', 'aplomb', 'apocalypse', 'apocalyptic', 'apologies', 'appalled', 'appalling', 'apparent', 'apparently', 'appeal', 'appealing', 'appeals', 'appear', 'appearance', 'appearances', 'appeared', 'appearing', 'appears', 'applaud', 'applause', 'apple', 'applied', 'applies', 'apply', 'appreciate', 'appreciated', 'appreciation', 'apprentice', 'approach', 'approached', 'approaches', 'approaching', 'appropriate', 'appropriately', 'approval', 'approved', 'approximately', 'april', 'apt', 'aptly', 'arab', 'arc', 'arch', 'archer', 'archive', 'are', 'area', 'areas', 'aren', 'arguably', 'argue', 'arguing', 'argument', 'arguments', 'ariel', 'arise', 'arizona', 'arjun', 'ark', 'arkin', 'arm', 'armageddon', 'armed', 'armor', 'arms', 'armstrong', 'army', 'arnie', 'arnold', 'around', 'aroused', 'arquette', 'arranged', 'array', 'arrest', 'arrested', 'arrival', 'arrive', 'arrived', 'arrives', 'arriving', 'arrogance', 'arrogant', 'arrow', 'art', 'artemisia', 'arthur', 'article', 'artificial', 'artist', 'artistic', 'artistry', 'artists', 'arts', 'artsy', 'artwork', 'arty', 'as', 'ash', 'ashamed', 'ashley', 'asia', 'asian', 'aside', 'ask', 'asked', 'askey', 'asking', 'asks', 'asleep', 'aspect', 'aspects', 'aspirations', 'aspiring', 'ass', 'assassin', 'assassination', 'assassins', 'assault', 'assembled', 'asset', 'assigned', 'assignment', 'assist', 'assistance', 'assistant', 'associate', 'associated', 'association', 'assorted', 'assume', 'assumed', 'assumes', 'assuming', 'assure', 'assured', 'astaire', 'astonished', 'astonishing', 'astonishingly', 'astounding', 'astronauts', 'asylum', 'at', 'ate', 'athletic', 'atlantis', 'atmosphere', 'atmospheric', 'atomic', 'atrocious', 'atrocities', 'atrocity', 'attached', 'attachment', 'attack', 'attacked', 'attacking', 'attacks', 'attempt', 'attempted', 'attempting', 'attempts', 'attenborough', 'attend', 'attendant', 'attended', 'attending', 'attends', 'attention', 'attic', 'attitude', 'attitudes', 'attorney', 'attract', 'attracted', 'attraction', 'attractive', 'attributed', 'attributes', 'audience', 'audiences', 'audio', 'audition', 'audrey', 'august', 'aunt', 'aunts', 'aussie', 'austen', 'austin', 'australia', 'australian', 'austria', 'auteur', 'authentic', 'authenticity', 'author', 'authorities', 'authority', 'authors', 'auto', 'autobiography', 'automatic', 'automatically', 'available', 'avenge', 'average', 'avid', 'avoid', 'avoided', 'avoiding', 'avoids', 'awaiting', 'awake', 'awakening', 'awakens', 'award', 'awarded', 'awards', 'aware', 'awareness', 'away', 'awe', 'aweigh', 'awesome', 'awful', 'awfully', 'awfulness', 'awhile', 'awkward', 'awkwardly', 'axe', 'azumi', 'babe', 'babes', 'babies', 'baby', 'babysitter', 'bacall', 'bach', 'bachchan', 'bachelor', 'back', 'backdrop', 'backed', 'background', 'backgrounds', 'backs', 'backwards', 'backwoods', 'bacon', 'bad', 'baddie', 'baddies', 'badly', 'badness', 'baffling', 'bag', 'bagdad', 'bait', 'baked', 'baker', 'bakshi', 'balance', 'balanced', 'balcony', 'bald', 'baldwin', 'ball', 'ballet', 'balloon', 'balls', 'banal', 'band', 'bands', 'bang', 'bank', 'banks', 'banned', 'banter', 'bar', 'barbara', 'barbra', 'bare', 'barely', 'bargain', 'barker', 'barman', 'barnes', 'barney', 'barrel', 'barry', 'barrymore', 'bars', 'bart', 'base', 'baseball', 'based', 'basement', 'bash', 'bashing', 'basic', 'basically', 'basil', 'basinger', 'basis', 'basketball', 'bastard', 'bat', 'bates', 'bath', 'bathing', 'bathroom', 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'spouse', 'spray', 'spread', 'spree', 'spring', 'springer', 'sprinkled', 'spy', 'squad', 'square', 'squirm', 'sr', 'st', 'stab', 'stabbed', 'stabbing', 'stabs', 'stack', 'stadium', 'staff', 'stage', 'staged', 'stages', 'staging', 'stairs', 'stairway', 'stake', 'stakes', 'stale', 'stalked', 'stalker', 'stalking', 'stalks', 'stallone', 'stan', 'stance', 'stand', 'standard', 'standards', 'standing', 'standout', 'standpoint', 'stands', 'stanley', 'stanwyck', 'star', 'stardom', 'stardust', 'stare', 'stares', 'stargate', 'staring', 'stark', 'starred', 'starring', 'stars', 'starship', 'start', 'started', 'starters', 'starting', 'startling', 'starts', 'starving', 'state', 'stated', 'statement', 'statements', 'states', 'static', 'stating', 'station', 'stations', 'statue', 'status', 'stay', 'stayed', 'staying', 'stays', 'steady', 'steal', 'stealing', 'steals', 'stealth', 'steam', 'steaming', 'steamy', 'steel', 'steele', 'steer', 'stella', 'stellar', 'step', 'stephanie', 'stephen', 'stepmother', 'stepped', 'steps', 'stereotype', 'stereotyped', 'stereotypes', 'stereotypical', 'sterling', 'stern', 'steve', 'steven', 'stevens', 'stevenson', 'stewart', 'stick', 'sticking', 'sticks', 'stiff', 'stifler', 'stiles', 'still', 'stiller', 'stills', 'stilted', 'stimulating', 'stink', 'stinker', 'stinks', 'stirring', 'stock', 'stoic', 'stole', 'stolen', 'stoltz', 'stomach', 'stone', 'stoned', 'stones', 'stood', 'stooges', 'stop', 'stopped', 'stopping', 'stops', 'store', 'stores', 'stories', 'storm', 'story', 'storyline', 'storytelling', 'straight', 'straightforward', 'strain', 'strained', 'stranded', 'strange', 'strangely', 'stranger', 'strangers', 'strathairn', 'straw', 'streak', 'stream', 'streep', 'street', 'streets', 'streisand', 'strength', 'strengths', 'stress', 'stretch', 'stretched', 'stretching', 'stricken', 'strict', 'strictly', 'strike', 'strikes', 'striking', 'strikingly', 'string', 'strings', 'strip', 'stripped', 'stripper', 'stroke', 'strong', 'stronger', 'strongest', 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'suggest', 'suggested', 'suggesting', 'suggestion', 'suggests', 'suicide', 'suit', 'suitable', 'suitably', 'suite', 'suited', 'suits', 'sullivan', 'sum', 'summary', 'summed', 'summer', 'sums', 'sun', 'sundance', 'sunday', 'sung', 'sunk', 'sunny', 'sunrise', 'sunset', 'sunshine', 'super', 'superb', 'superbly', 'superficial', 'superfluous', 'superhero', 'superior', 'superiors', 'superman', 'supermarket', 'supernatural', 'superstar', 'supply', 'support', 'supported', 'supporter', 'supporting', 'supportive', 'supports', 'suppose', 'supposed', 'supposedly', 'supremacy', 'supreme', 'sure', 'surely', 'surface', 'surfers', 'surfing', 'surgeon', 'surgery', 'surprise', 'surprised', 'surprises', 'surprising', 'surprisingly', 'surreal', 'surrealism', 'surrender', 'surrogate', 'surround', 'surrounded', 'surrounding', 'surroundings', 'survival', 'survive', 'survived', 'survives', 'surviving', 'survivor', 'survivors', 'susan', 'susannah', 'suspect', 'suspected', 'suspects', 'suspend', 'suspense', 'suspenseful', 'suspension', 'suspicion', 'suspicions', 'suspicious', 'sustain', 'sustained', 'sutherland', 'suzanne', 'swallow', 'swanson', 'swear', 'swearing', 'sweat', 'sweden', 'swedish', 'sweeping', 'sweet', 'swept', 'swim', 'swimming', 'swing', 'swinging', 'swiss', 'switch', 'switched', 'switches', 'switching', 'sword', 'swordplay', 'swords', 'sydney', 'sykes', 'sylvester', 'sylvia', 'symbol', 'symbolic', 'symbolism', 'symbols', 'sympathetic', 'sympathize', 'sympathy', 'sync', 'syndrome', 'synopsis', 'system', 'systems', 'table', 'tables', 'taboo', 'tacked', 'tacky', 'tactics', 'tad', 'tag', 'tail', 'takashi', 'take', 'taken', 'taker', 'takes', 'taking', 'tale', 'talent', 'talented', 'talents', 'tales', 'talk', 'talked', 'talking', 'talks', 'talky', 'tall', 'tame', 'tank', 'tanks', 'tap', 'tape', 'taped', 'tapes', 'tara', 'tarantino', 'target', 'targeted', 'targets', 'tarkovsky', 'tarzan', 'task', 'tasks', 'tassi', 'taste', 'tasteful', 'tasteless', 'tastes', 'tasty', 'taught', 'taut', 'tax', 'taxi', 'taylor', 'tcm', 'tea', 'teach', 'teacher', 'teachers', 'teaches', 'teaching', 'team', 'teamed', 'teams', 'tear', 'tears', 'tech', 'technical', 'technically', 'technicolor', 'technique', 'techniques', 'technology', 'ted', 'teddy', 'tedious', 'teen', 'teenage', 'teenager', 'teenagers', 'teens', 'teeth', 'television', 'tell', 'telling', 'tells', 'telly', 'temper', 'tempered', 'temple', 'temporary', 'tempted', 'ten', 'tenant', 'tend', 'tended', 'tendency', 'tender', 'tenderness', 'tends', 'tense', 'tension', 'term', 'terminator', 'terms', 'terrain', 'terrible', 'terribly', 'terrific', 'terrified', 'terrifying', 'territory', 'terror', 'terrorism', 'terrorist', 'terrorists', 'terrorized', 'terry', 'tess', 'test', 'testament', 'tested', 'testimony', 'testing', 'texas', 'text', 'textbook', 'texture', 'thai', 'thailand', 'than', 'thank', 'thankful', 'thankfully', 'thankless', 'thanks', 'that', 'thats', 'thaw', 'the', 'theater', 'theaters', 'theatre', 'theatrical', 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'track', 'tracking', 'tracks', 'tracy', 'trade', 'trademark', 'tradition', 'traditional', 'traditions', 'traffic', 'tragedy', 'tragic', 'trail', 'trailer', 'trailers', 'train', 'trained', 'training', 'trains', 'traits', 'tramp', 'trance', 'transcends', 'transfer', 'transform', 'transformation', 'transformations', 'transformed', 'transformers', 'transforms', 'transition', 'transitions', 'translate', 'translated', 'translation', 'transparent', 'transplant', 'transport', 'transported', 'trap', 'trapped', 'traps', 'trash', 'trashy', 'trauma', 'traumatic', 'traumatized', 'travel', 'traveled', 'traveling', 'travelling', 'travels', 'travesty', 'travis', 'travolta', 'treasure', 'treat', 'treated', 'treating', 'treatment', 'treats', 'tree', 'trees', 'trek', 'tremendous', 'tremendously', 'trend', 'trendy', 'triad', 'trial', 'trials', 'triangle', 'tribe', 'tribute', 'trick', 'tricked', 'tricks', 'tricky', 'tried', 'trier', 'tries', 'trigger', 'trilogy', 'trio', 'trip', 'tripe', 'triple', 'trish', 'trite', 'triumph', 'triumphs', 'trivia', 'trivial', 'troma', 'troopers', 'troops', 'trouble', 'troubled', 'troubles', 'truck', 'true', 'truly', 'truman', 'trust', 'trusted', 'truth', 'truthful', 'truths', 'try', 'trying', 'tube', 'tucci', 'tucker', 'tune', 'tunes', 'tunnel', 'turd', 'turkey', 'turkish', 'turmoil', 'turn', 'turned', 'turner', 'turning', 'turns', 'turtle', 'turturro', 'tv', 'twelve', 'twentieth', 'twenty', 'twice', 'twilight', 'twin', 'twins', 'twist', 'twisted', 'twists', 'twitch', 'two', 'tyler', 'type', 'types', 'typical', 'typically', 'uber', 'ugh', 'ugly', 'uh', 'uk', 'ultimate', 'ultimately', 'ultimatum', 'ultra', 'um', 'uma', 'un', 'unable', 'unanswered', 'unappealing', 'unattractive', 'unaware', 'unbearable', 'unbelievable', 'unbelievably', 'uncanny', 'uncertain', 'uncle', 'unclear', 'uncomfortable', 'unconscious', 'unconventional', 'unconvincing', 'uncut', 'undead', 'undeniably', 'under', 'undercover', 'underdeveloped', 'underdog', 'underground', 'underlying', 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'voyager', 'vs', 'vulgar', 'vulnerable', 'wacky', 'wagner', 'wait', 'waited', 'waiting', 'waitress', 'waits', 'wake', 'wakes', 'waking', 'walk', 'walked', 'walken', 'walker', 'walking', 'walks', 'wall', 'wallace', 'wallach', 'walls', 'wally', 'walsh', 'walt', 'walter', 'walters', 'wan', 'wander', 'wandering', 'wanders', 'wang', 'wanna', 'wannabe', 'want', 'wanted', 'wanting', 'wants', 'waqt', 'war', 'ward', 'warden', 'wardrobe', 'warehouse', 'warfare', 'warhols', 'warm', 'warming', 'warmth', 'warn', 'warned', 'warner', 'warning', 'warnings', 'warns', 'warrant', 'warren', 'warrior', 'warriors', 'wars', 'wartime', 'was', 'wash', 'washed', 'washington', 'wasn', 'waste', 'wasted', 'wastes', 'wasting', 'watch', 'watchable', 'watched', 'watcher', 'watchers', 'watches', 'watching', 'water', 'watered', 'waterfall', 'waterfront', 'waters', 'watson', 'watts', 'wave', 'waves', 'waving', 'wax', 'way', 'wayans', 'wayne', 'ways', 'we', 'weak', 'weaker', 'weakest', 'weakness', 'weaknesses', 'wealth', 'wealthy', 'weapon', 'weapons', 'wear', 'wearing', 'wears', 'weary', 'weather', 'weaver', 'web', 'website', 'wedding', 'wee', 'week', 'weekend', 'weekly', 'weeks', 'weight', 'weird', 'weirdness', 'welch', 'welcome', 'welcomed', 'well', 'welles', 'wells', 'wendigo', 'wendt', 'wendy', 'went', 'wentworth', 'were', 'weren', 'werewolf', 'werewolves', 'werner', 'wes', 'wesley', 'west', 'western', 'westerns', 'wet', 'whacked', 'whale', 'what', 'whatever', 'whats', 'whatsoever', 'wheel', 'wheelchair', 'wheeler', 'when', 'whenever', 'where', 'whereas', 'wherein', 'wherever', 'whether', 'which', 'while', 'whilst', 'whimsical', 'whining', 'whiny', 'whip', 'whipped', 'white', 'whites', 'who', 'whoever', 'whole', 'wholesome', 'wholly', 'whom', 'whoopi', 'whore', 'whose', 'why', 'wicked', 'wicker', 'wide', 'widely', 'wider', 'widescreen', 'widmark', 'widow', 'widowed', 'widower', 'wielding', 'wife', 'wig', 'wild', 'wilder', 'wilderness', 'wildly', 'will', 'willem', 'william', 'williams', 'willie', 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'wounds', 'wow', 'wrap', 'wrapped', 'wraps', 'wray', 'wreck', 'wrenching', 'wrestler', 'wrestling', 'wretched', 'wright', 'wrist', 'write', 'writer', 'writers', 'writes', 'writing', 'written', 'wrong', 'wrongly', 'wrote', 'wrought', 'wtc', 'wtf', 'wu', 'ww2', 'wwe', 'wwf', 'wwi', 'wwii', 'www', 'ya', 'yacht', 'yard', 'yarn', 'yawn', 'yeah', 'year', 'yearning', 'years', 'yell', 'yelling', 'yellow', 'yells', 'yep', 'yes', 'yesterday', 'yet', 'yeti', 'yikes', 'yoda', 'yokai', 'york', 'you', 'young', 'younger', 'youngest', 'youngsters', 'your', 'yours', 'yourself', 'youth', 'youthful', 'youths', 'youtube', 'yuen', 'yugoslavia', 'yuma', 'zack', 'zane', 'zealand', 'zelah', 'zenia', 'zentropa', 'zero', 'zeta', 'zhang', 'zizek', 'zodiac', 'zoe', 'zombi', 'zombie', 'zombies', 'zone', 'zoo', 'zoom', 'zorro', 'zu']


Vocabulary
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'particularly': 6465, 'fascinated': 3382, 'minister': 5758, 'father': 3398, 'figure': 3478, 'camp': 1372, 'fetched': 3450, 'lonely': 5346, 'depression': 2512, 'trying': 9271, 'survive': 8759, 'type': 9303, 'winds': 9821, 'touching': 9143, 'tale': 8834, 'kudos': 5070, 'writers': 9926, 'creating': 2186, 'drama': 2794, 'curious': 2275, 'development': 2577, 'nuanced': 6164, 'team': 8879, 'wrenching': 9918, 'emotional': 3023, 'cerebral': 1525, 'opportunity': 6288, 'develop': 2574, 'herself': 4273, 'rarely': 7148, 'credit': 2197, 'breathing': 1204, 'wood': 9878, 'shop': 8044, 'persona': 6568, 'unfolds': 9371, 'traits': 9181, 'faults': 3401, 'variety': 9486, 'highly': 4290, 'charged': 1569, 'relationships': 7300, 'course': 2144, 'fate': 3396, 'tied': 9049, 'principals': 6895, 'catch': 1479, 'house': 4405, 'retired': 7437, 'michael': 5714, 'york': 9964, 'goes': 3933, 'russia': 7646, 'revenge': 7455, 'russian': 7647, 'gangster': 3794, 'murdered': 5936, 'policeman': 6731, 'son': 8299, 'meets': 5650, 'exceptionally': 3216, 'strong': 8597, 'decent': 2403, 'cop': 2089, 'bring': 1229, 'justice': 4943, 'remembered': 7337, '1980s': 68, 'always': 432, 'portray': 6769, 'russians': 7648, 'guys': 4088, 'righteous': 7502, 'guy': 4087, 'typically': 9306, 'lends': 5203, 'class': 1718, 'mediocre': 5644, 'alexander': 385, 'blah': 1036, 'surprisingly': 8749, 'chemistry': 1609, 'handsome': 4131, 'adrian': 285, 'killed': 5011, 'within': 9850, '15': 11, 'above': 164, 'villain': 9553, 'blonde': 1069, 'villainous': 9554, 'rent': 7358, 'okay': 6249, 'suck': 8672, 'faster': 3392, 'load': 5321, 'wasted': 9680, 'commercials': 1876, '30': 116, 'ad': 244, 'makeup': 5476, 'ass': 670, 'ed': 2933, 'least': 5178, 'imagine': 4514, 'white': 9778, 'teeth': 8899, 'dentist': 2491, 'gotten': 3967, 'self': 7869, 'lousy': 5382, 'ads': 286, 'chance': 1545, 'instead': 4685, 'pilot': 6641, 'lacked': 5085, 'option': 6294, 'pray': 6820, 'death': 2388, 'episodes': 3122, 'deserving': 2536, 'david': 2364, 'mamet': 5486, 'directorial': 2639, 'debut': 2396, 'games': 3788, 'study': 8618, 'psychological': 7005, 'overtones': 6370, 'psychiatrist': 7002, 'lured': 5420, 'confidence': 1965, 'game': 3786, 'margaret': 5520, 'ford': 3634, 'lindsay': 5279, 'crouse': 2240, 'practice': 6814, 'written': 9929, 'selling': 7874, 'somewhat': 8297, 'neither': 6045, 'define': 2431, 'nor': 6122, 'resolve': 7407, 'steven': 8520, 'session': 7929, 'owes': 6377, 'pay': 6508, 'decides': 2408, 'takes': 8832, 'seedy': 7850, 'dive': 2717, 'mike': 5729, 'joe': 4885, 'charismatic': 1572, 'con': 1939, 'wastes': 9681, 'claimed': 1707, 'owed': 6375, 'turns': 9286, 'eight': 2970, 'hundred': 4435, 'dollars': 2743, 'agrees': 342, 'wipe': 9834, 'clean': 1731, 'agree': 340, 'simple': 8116, 'favor': 3403, 'involves': 4767, 'card': 1420, 'hand': 4122, 'gone': 3943, 'hooked': 4366, 'precise': 6827, 'deliver': 2456, 'mesmerizing': 5694, 'leads': 5168, 'compelling': 1903, 'surreal': 8750, 'realm': 7202, 'existence': 3240, 'introduces': 4746, 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8458, 'kramer': 5062, 'involved': 4765, 'mess': 5695, 'summed': 8702, 'happens': 4146, 'washed': 9676, 'stars': 8470, 'late': 5129, '1990': 78, 'launch': 5142, 'comeback': 1852, 'reunion': 7446, 'tour': 9145, 'members': 5666, 'fruit': 3734, 'fictional': 3461, '70': 136, 'tony': 9114, 'rea': 7170, 'machines': 5437, 'runs': 7639, 'famous': 3363, 'festival': 3448, 'broke': 1242, 'retro': 7440, 'wide': 9792, 'wave': 9697, 'sets': 7932, 'search': 7820, 'keith': 4980, 'writer': 9925, 'excessive': 3219, 'lifestyle': 5247, 'timothy': 9066, 'lies': 5243, 'player': 6686, 'rocker': 7553, 'owns': 6383, 'mansion': 5512, 'forced': 3631, 'sell': 7871, 'fortune': 3666, 'lasted': 5125, 'hired': 4311, 'replace': 7369, 'reluctantly': 7321, 'try': 9270, 'jobs': 4882, 'begin': 920, 'manager': 5491, 'approaches': 586, 'label': 5078, 'albums': 378, 'club': 1781, 'overweight': 6371, 'starts': 8477, 'conflicts': 1972, 'figures': 3480, 'hang': 4133, 'second': 7833, 'greatness': 4014, 'earlier': 2905, 'crazy': 2181, 'spinal': 8382, 'tap': 8848, 'ii': 4494, 'gradually': 3979, 'becomes': 905, 'dramatically': 2797, 'focused': 3600, 'struggling': 8607, 'deal': 2380, 'deaths': 2389, 'demons': 2476, 'killing': 5014, 'depicted': 2505, 'happen': 4142, 'truth': 9267, 'carried': 1452, 'teenagers': 8897, 'cal': 1355, 'andre': 477, 'normal': 6126, 'using': 9454, 'held': 4239, 'technique': 8888, 'la': 5076, 'blair': 1037, 'witch': 9845, 'ben': 953, 'succeeds': 8666, 'bringing': 1230, 'issues': 4802, 'exactly': 3201, 'hate': 4184, 'carry': 1454, 'thought': 9008, 'massacre': 5568, 'shooting': 8041, 'powerful': 6809, 'happening': 4144, 'happened': 4143, 'creates': 2185, 'illusion': 4502, 'scripted': 7807, 'subject': 8641, 'matter': 5591, 'deadly': 2377, 'bloody': 1075, 'violent': 9562, 'super': 8714, 'ninjas': 6096, 'features': 3420, 'fight': 3473, 'hong': 4361, 'kong': 5057, 'considered': 2005, 'masterpiece': 5576, 'launched': 5143, 'careers': 1426, 'men': 5671, 'play': 6683, 'lo': 5319, 'philip': 6601, 'boiled': 1101, 'chop': 1650, 'ain': 356, 'collect': 1822, 'bob': 1092, 'strength': 8578, 'blade': 1035, 'plan': 6669, 'inevitable': 4612, 'odd': 6218, 'turkey': 9279, 'realise': 7187, 'knock': 5046, 'folks': 3609, 'guess': 4063, 'needed': 6030, 'career': 1425, 'painful': 6401, 'undeniably': 9337, 'save': 7730, 'special': 8354, 'laden': 5090, 'junk': 4939, 'fast': 3391, 'furious': 3760, 'push': 7042, 'favorite': 3404, 'tom': 9099, 'jerry': 4861, 'perfect': 6546, 'halloween': 4114, 'creepiness': 2202, 'trick': 9236, 'window': 9819, 'blind': 1060, 'cleaner': 1733, 'shirt': 8027, 'hanging': 4134, 'ghost': 3867, 'cartoons': 1460, 'listening': 5301, 'program': 6935, 'radio': 7098, 'frightened': 3725, 'standing': 8454, 'throat': 9027, 'icy': 4468, 'chills': 1635, 'spine': 8383, 'literally': 5305, 'laughing': 5139, 'fears': 3415, 'scaring': 7754, 'four': 3676, 'attacks': 714, 'shoes': 8038, 'mouse': 5906, 'witty': 9857, 'kitty': 5036, 'speaks': 8353, 'cat': 1478, 'million': 5740, 'dollar': 2742, 'bodyguard': 1096, 'trouble': 9258, 'quiet': 7074, 'please': 6694, 'trap': 9201, 'happy': 4149, 'solid': 8280, 'cleaning': 1734, 'texas': 8942, 'below': 950, 'chuck': 1676, 'jones': 4904, 'spy': 8422, 'thriller': 9023, 'night': 6085, 'vonnegut': 9603, 'novels': 6157, 'adapt': 248, 'length': 5204, 'adaptation': 249, 'faithful': 3349, 'indie': 4599, 'approach': 584, 'produced': 6916, 'effective': 2955, 'hollywood': 4343, 'intelligent': 4702, 'green': 4019, 'normally': 6127, 'direction': 2635, 'nick': 6079, 'nolte': 6110, 'older': 6252, 'allows': 411, 'range': 7130, 'lee': 5186, 'deserved': 2533, 'industry': 4610, 'twin': 9295, 'peaks': 6520, 'air': 357, 'phenomenon': 6598, 'read': 7178, 'realities': 7194, 'premise': 6847, 'appear': 568, 'knowledge': 5052, 'utterly': 9459, 'confused': 1979, 'events': 3177, 'unfolding': 9370, 'fellow': 3436, 'americans': 450, 'lowest': 5395, 'lord': 5362, 'knows': 5054, 'subjects': 8643, 'morgan': 5874, 'freeman': 3709, 'spanish': 8345, 'paz': 6514, 'vega': 9496, 'whilst': 9772, 'independent': 4592, 'dubious': 2853, 'positive': 6782, 'contain': 2022, 'plots': 6704, 'easy': 2921, 'follow': 3610, 'saddest': 7663, 'smile': 8234, 'need': 6029, 'petty': 6591, 'cliché': 1743, 'sides': 8088, 'laughter': 5141, 'rare': 7147, 'forward': 3669, 'jan': 4831, 'vincent': 9557, 'nut': 6177, 'affair': 305, 'helicopters': 4243, 'fantasy': 3371, 'unbelievable': 9325, 'speed': 8365, 'record': 7233, 'experimental': 3262, '1960': 47, '300': 117, 'compound': 1931, 'providing': 6994, 'thrust': 9037, 'wing': 9823, 'period': 6559, 'called': 1360, 'blue': 1082, 'realistic': 7192, 'carrey': 1450, 'haven': 4195, 'bruce': 1257, 'almighty': 414, 'none': 6115, 'reviews': 7464, 'dont': 2756, 'somehow': 8291, 'attempt': 715, 'liar': 5237, 'daily': 2307, 'steve': 8519, 'hilarious': 4292, 'jim': 4877, 'hearted': 4222, 'piano': 6625, 'example': 3206, 'storytelling': 8560, 'superb': 8715, 'inspiring': 4679, 'manipulative': 5503, 'fake': 3350, 'tad': 8825, 'considering': 2006, 'restraint': 7428, 'single': 8134, 'explosion': 3287, 'suspenseful': 8772, 'thus': 9044, 'extraordinary': 3307, 'words': 9883, 'describe': 2524, 'terrible': 8924, 'dull': 2867, 'lifeless': 5246, 'laugh': 5135, 'response': 7420, 'posters': 6795, 'anne': 509, 'marie': 5522, 'highlight': 4287, 'person': 6567, 'brett': 1214, 'kelly': 4983, 'statement': 8481, 'male': 5479, 'sister': 8145, 'brother': 1252, 'gal': 3781, 'opposite': 6290, 'attractive': 733, 'tall': 8844, 'holding': 4335, 'mark': 5530, 'rain': 7106, 'forest': 3638, 'keep': 4974, 'perfectly': 6548, 'kidnapped': 5007, 'steps': 8512, 'poo': 6746, 'solve': 8284, 'felt': 3437, 'rental': 7359, 'home': 4348, 'gave': 3818, 'marks': 5535, 'besides': 975, 'lack': 5084, 'constant': 2013, 'aided': 348, 'joke': 4896, 'utter': 9458, 'waste': 9679, 'sounds': 8328, 'promising': 6956, 'tube': 9272, 'meant': 5631, 'racist': 7093, 'result': 7429, 'creative': 2189, 'desperately': 2547, 'almost': 415, 'hear': 4216, 'crying': 2257, 'ugly': 9309, 'mexican': 5707, 'racism': 7092, 'charges': 1570, 'aside': 659, 'pile': 6640, 'beans': 884, 'offended': 6228, 'imo': 4529, 'breathtaking': 1206, 'donald': 2753, 'woods': 9880, 'south': 8334, 'apartheid': 552, 'kevin': 4992, 'kline': 5037, 'convincing': 2079, 'appeared': 571, 'denzel': 2495, 'washington': 9677, 'masterful': 5573, 'urge': 9442, 'patience': 6493, 'tells': 8903, 'incredible': 4588, 'seven': 7939, 'pounds': 6803, 'cry': 2256, 'smith': 8237, 'tune': 9275, 'vast': 9490, 'emotion': 3022, 'beautifully': 897, 'intense': 4706, 'humanity': 4428, 'compare': 1895, 'crash': 2171, 'raw': 7164, 'sticks': 8526, 'gives': 3895, 'deep': 2420, 'passion': 6481, 'exists': 3243, 'abundance': 179, 'therefore': 8980, 'pain': 6400, 'sometimes': 8296, 'lost': 5374, 'deeper': 2421, 'silent': 8104, 'indicate': 4597, 'dubbing': 2852, 'review': 7459, 'rene': 7356, 'lovely': 5386, 'reputation': 7388, 'maker': 5473, 'louise': 5381, 'brooks': 1249, 'ways': 9704, 'technically': 8886, 'switched': 8797, 'mode': 5818, '30s': 119, 'french': 3712, 'dialog': 2589, 'slapped': 8183, 'lip': 5293, 'movements': 5913, 'particular': 6464, 'come': 1851, 'explain': 3268, 'ms': 5921, 'preferred': 6839, 'morality': 5865, '1930': 19, 'slutty': 8222, 'wins': 9830, 'contest': 2032, 'macho': 5438, 'handle': 4126, 'fancy': 3367, 'spells': 8370, 'melodramatic': 5660, 'huh': 4423, 'underdeveloped': 9340, 'harold': 4167, 'lloyd': 5318, 'abused': 181, 'picked': 6627, 'took': 9116, 'resolution': 7406, 'superfluous': 8718, 'treatment': 9221, 'received': 7218, 'spirited': 8387, 'audiences': 737, 'implied': 4536, 'le': 5162, 'femme': 3442, 'du': 2849, 'rating': 7154, 'ned': 6028, 'wonderfully': 9870, 'australian': 748, 'taken': 8830, 'byrne': 1343, 'gang': 3792, 'explains': 3271, 'actions': 232, 'exceptional': 3215, 'stellar': 8506, 'brings': 1231, 'heath': 4227, 'orlando': 6315, 'bloom': 1076, 'fantastic': 3370, 'loyal': 5397, 'believed': 940, 'win': 9816, 'battle': 873, 'alas': 373, 'aspects': 667, 'avid': 764, 'supporter': 8729, 'slightly': 8210, 'disappointed': 2653, 'cover': 2151, 'covered': 2153, 'regardless': 7275, 'flaws': 3559, 'moving': 5917, 'sorts': 8320, 'emotions': 3025, 'assume': 686, 'mick': 5718, 'jagger': 4825, 'shelley': 8007, 'duvall': 2885, 'theatre': 8960, 'broadway': 1240, 'relief': 7316, 'eve': 3172, 'wicked': 9790, 'jennifer': 4856, 'cinderella': 1684, 'garden': 3803, 'matthew': 5594, 'prince': 6892, 'charming': 1579, 'jean': 4849, 'fairy': 3346, 'southern': 8335, 'martin': 5552, 'royal': 7618, 'orchestra': 6297, 'conductor': 1961, 'tiny': 9069, 'flow': 3587, 'comments': 1874, 'thrown': 9034, 'children': 1631, 'flows': 3591, 'happily': 4147, 'age': 329, 'continue': 2038, 'parents': 6446, 'tired': 9073, 'near': 6018, 'shootout': 8042, 'horses': 4393, 'red': 7243, 'catches': 1480, 'eye': 3313, 'bush': 1322, 'trail': 9174, 'western': 9751, 'paid': 6399, 'buddies': 1274, 'grand': 3987, 'slow': 8217, 'seriously': 7917, 'filming': 3490, 'door': 2761, 'move': 5910, 'cabin': 1346, 'peoples': 6539, 'praised': 6817, 'titles': 9079, 'season': 7824, 'episode': 3121, 'proper': 6967, 'investigation': 4757, 'agent': 333, 'cooper': 2088, 'throws': 9035, 'stones': 8547, 'bottle': 1150, 'identify': 4476, 'murderer': 5937, 'mentioning': 5680, 'supernatural': 8724, 'ability': 156, 'unnecessary': 9405, 'serves': 7924, 'cup': 2272, 'milk': 5736, 'laying': 5159, 'floor': 3581, 'gun': 4076, 'shoots': 8043, 'belly': 946, 'min': 5743, 'hell': 4244, 'comic': 1861, 'enemies': 3059, 'content': 2031, 'improvement': 4554, 'airplane': 361, 'triangle': 9233, 'sinks': 8140, 'post': 6792, 'submarine': 8645, 'casts': 1475, 'falling': 3354, 'barely': 841, 'horizon': 4380, 'our': 6331, 'kennedy': 4985, 'airport': 362, 'stuck': 8610, 'phoenix': 6607, 'nyc': 6182, 'politics': 6741, 'seemingly': 7858, 'foot': 3623, 'expect': 3248, 'continues': 2040, 'cusack': 2285, 'accent': 185, 'laughable': 5136, 'horrible': 4384, 'military': 5735, 'training': 9179, 'becoming': 906, 'genre': 3842, 'prominent': 6952, 'officer': 6237, 'gentleman': 3845, 'jane': 4832, 'honor': 4362, 'focuses': 3601, 'angle': 491, 'inspirational': 4676, 'interest': 4718, 'mentioned': 5679, 'carl': 1437, 'brashear': 1186, 'cuba': 2260, 'gooding': 3948, 'courage': 2142, 'shines': 8021, 'tunnel': 9277, 'vision': 9576, 'presenting': 6858, 'showing': 8070, 'adversity': 297, 'sunday': 8707, 'niro': 6097, 'central': 1520, 'initial': 4645, 'instance': 4681, 'hal': 4109, 'judge': 4918, 'pacing': 6388, 'ranting': 7137, 'needs': 6034, 'rises': 7517, 'occasion': 6205, 'rod': 7558, 'fascinating': 3383, 'dimensional': 2625, 'depth': 2513, 'faces': 3322, 'challenging': 1539, 'chill': 1632, 'suicide': 8692, 'comedian': 1853, 'analyze': 470, 'adventures': 295, 'rocky': 7557, 'meet': 5648, 'deniro': 2483, 'roots': 7595, 'personality': 6571, 'tortured': 9134, 'soul': 8323, 'pleasure': 6697, 'lately': 5130, 'legend': 5191, 'vance': 9477, 'wonder': 9867, 'step': 8507, 'co': 1791, 'gere': 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'sounded': 8326, 'portraying': 6773, 'puppets': 7029, 'creepy': 2203, 'rob': 7535, 'grant': 3995, 'doug': 2771, 'dwarf': 2888, 'comment': 1870, 'robbed': 7536, 'borrowed': 1140, 'returned': 7443, 'demand': 2465, 'warrant': 9668, 'heard': 4217, 'bay': 879, 'turner': 9284, 'tonight': 9112, 'oscar': 6320, 'month': 5854, 'winning': 9829, 'sequel': 7905, 'success': 8667, 'mary': 5560, 'winner': 9827, 'julie': 4929, 'andrews': 480, 'wherein': 9767, 'mixture': 5808, 'past': 6484, 'british': 1235, 'london': 5343, 'england': 3070, 'summer': 8703, '1940': 30, 'owen': 6376, 'general': 3831, 'guard': 4059, 'whereas': 9766, 'formerly': 3655, 'boom': 1124, 'ironically': 4781, 'final': 3498, 'reminds': 7344, 'dad': 2302, 'dealing': 2382, 'problems': 6909, 'war': 9652, 'suggested': 8688, 'appearance': 569, 'three': 9019, 'disney': 2689, 'fashion': 3387, 'road': 7534, 'soldiers': 8277, 'india': 4593, 'metal': 5702, 'scottish': 7788, 'female': 3438, 'costume': 2123, 'angela': 484, 'lansbury': 5113, 'price': 6883, 'sole': 8278, 'noteworthy': 6144, 'shortly': 8052, 'brief': 1222, 'balloon': 827, 'boys': 1172, 'picture': 6632, 'gray': 4008, 'yellow': 9954, 'bird': 1016, 'support': 8727, 'harvey': 4180, 'girls': 3892, 'santa': 7704, 'dennis': 2487, 'learning': 5175, 'rise': 7516, 'lifetime': 5248, 'relative': 7301, 'failure': 3339, 'cindy': 1685, 'roy': 7617, 'ian': 4463, 'predecessors': 6831, 'budding': 1275, 'surprising': 8748, 'possibly': 6791, 'cutting': 2293, 'roddy': 7559, 'witchcraft': 9846, 'bigger': 999, 'raid': 7102, 'imagined': 4515, 'countryside': 2135, 'sam': 7687, 'magic': 5454, 'seeking': 7853, 'sea': 7815, 'soccer': 8264, 'match': 5581, 'drawn': 2803, 'latter': 5134, 'glover': 3920, 'appreciate': 580, 'poetry': 6715, 'slide': 8207, 'choose': 1647, 'properly': 6968, 'drug': 2842, 'grey': 4029, 'gardens': 3804, 'enthralling': 3103, 'sad': 7662, 'beyond': 989, 'uncle': 9329, 'bathroom': 869, 'reader': 7179, 'eccentric': 2928, 'filmed': 3488, 'edie': 2940, 'outfits': 6340, 'include': 4573, 'nose': 6134, 'murder': 5935, 'rooms': 7591, 'joseph': 4907, 'sherlock': 8015, 'holmes': 4344, 'accurate': 210, 'excellently': 3211, 'digital': 2619, 'unusual': 9423, 'piece': 6635, 'round': 7607, 'tim': 9057, 'cox': 2161, 'name': 5985, 'impressed': 4545, 'twists': 9299, 'sci': 7772, 'fi': 3456, 'women': 9865, 'talked': 8840, 'disgusting': 2682, 'views': 9546, 'gender': 3829, 'lower': 5394, 'tolerance': 9096, 'depressing': 2511, 'whatever': 9757, 'cause': 1490, 'difference': 2609, 'begins': 922, 'subsequent': 8648, 'headed': 4210, 'charlton': 1577, 'heston': 4275, 'head': 4208, 'international': 4726, 'soylent': 8338, 'corporation': 2107, 'realize': 7197, 'gorgeous': 3958, 'security': 7844, 'pleasures': 6698, 'furniture': 3761, 'apartment': 553, 'masses': 5569, 'dirt': 2642, 'unemployed': 9361, 'abandoned': 151, 'cars': 1456, 'severe': 7943, 'indeed': 4590, 'died': 2605, 'discuss': 2670, 'edward': 2951, 'robinson': 7547, 'sidekick': 8087, 'depressed': 2510, 'allegorical': 402, 'profound': 6933, 'westerns': 9752, 'excruciatingly': 3228, 'impossible': 4543, 'emphasize': 3029, 'bland': 1043, 'violence': 9561, 'appalling': 562, 'convincingly': 2080, 'executed': 3231, 'flip': 3575, 'betrays': 980, 'ride': 7492, 'negative': 6036, 'verhoeven': 9509, 'garbage': 3800, 'hack': 4095, 'admission': 275, 'chapters': 1560, 'bored': 1134, 'scratch': 7789, 'supported': 8728, 'trash': 9204, 'alive': 397, 'basically': 859, 'steals': 8497, 'portion': 6765, 'idiot': 4480, 'anime': 504, 'pits': 6655, 'park': 6449, 'beloved': 949, 'moon': 5861, 'cheese': 1604, '22': 107, 'adventure': 294, 'earliest': 2906, 'reminiscent': 7345, 'box': 1162, 'admirable': 269, 'hugely': 4419, 'traditional': 9169, 'generation': 3835, 'aware': 776, 'shall': 7972, 'seek': 7852, 'popularity': 6756, 'recent': 7221, 'impressive': 4548, 'lacks': 5088, 'possess': 6784, 'fairly': 3344, 'standard': 8452, 'plain': 6668, 'centers': 1519, 'town': 9153, 'ernest': 3133, 'keller': 4981, 'psycho': 7004, 'offers': 6235, 'unseen': 9415, 'carries': 1453, 'bach': 796, 'consider': 2001, 'gem': 3826, 'images': 4509, 'hip': 4307, 'lie': 5242, 'claim': 1706, 'knowing': 5051, 'implies': 4537, 'cats': 1487, 'daddy': 2303, 'sit': 8147, 'noir': 6106, 'manage': 5488, 'sophistication': 8311, 'moody': 5860, 'phrase': 6618, 'foreboding': 3635, 'sidewalk': 8089, 'difficult': 2613, 'copy': 2094, 'manhattan': 5498, 'rough': 7605, 'cable': 1347, 'channel': 1553, 'belongs': 948, 'category': 1484, 'opening': 6275, 'curtain': 2283, 'drawing': 2801, 'rogue': 7564, 'loner': 5347, 'detective': 2565, 'marc': 5517, 'dixon': 2725, 'closer': 1770, 'threatening': 9017, 'familiar': 3359, 'dana': 2321, 'bleak': 1052, 'stare': 8463, 'troubled': 9259, 'intensity': 4708, 'uncomfortable': 9331, 'yeah': 9948, 'suspects': 8769, 'newly': 6069, 'promoted': 6958, 'karl': 4961, 'malden': 5478, 'outing': 6341, 'warning': 9665, 'hates': 4187, 'stop': 8550, 'rats': 7158, 'tough': 9144, 'boss': 1141, 'rolls': 7572, 'complaints': 1916, 'receiving': 7220, 'hook': 4365, 'advice': 300, 'matters': 5592, 'hands': 4130, 'finds': 3505, 'instincts': 4687, 'passed': 6477, 'cops': 2093, 'partner': 6469, 'questionable': 7069, 'threatens': 9018, 'bogart': 1097, 'escape': 3140, 'nowhere': 6161, 'turn': 9282, 'discovers': 2668, 'virtually': 9569, 'tierney': 9050, 'bachelor': 798, 'taut': 8868, 'gripping': 4037, 'polished': 6736, 'parody': 6454, 'fodder': 3603, 'sappy': 7706, 'notch': 6140, 'slick': 8206, 'considerable': 2002, 'gentle': 3844, 'heaven': 4229, 'grow': 4048, 'destruction': 2559, 'rope': 7596, 'cut': 2289, 'innocent': 4654, 'false': 3356, 'wildly': 9806, 'slight': 8208, 'shift': 8017, 'wind': 9818, 'punch': 7023, 'factors': 3328, 'control': 2054, 'darkest': 2347, 'surface': 8740, 'pick': 6626, 'sterling': 8517, 'dub': 2850, 'model': 5819, 'mystery': 5972, 'science': 7773, 'fans': 3368, 'heck': 4233, 'terrific': 8926, 'wit': 9844, 'pace': 6385, 'stopping': 8552, 'busby': 1319, 'numbers': 6170, 'ahead': 344, 'street': 8575, 'definitive': 2438, 'jimmy': 4878, 'cagney': 1351, 'releases': 7309, 'strictly': 8586, 'direct': 2632, 'references': 7258, 'trained': 9178, 'bother': 1146, 'wanting': 9649, 'become': 904, 'spotted': 8414, 'filmmaker': 3491, 'asked': 661, 'guessed': 4064, 'avoid': 765, 'overlook': 6362, 'idiotic': 4481, 'occurring': 6214, 'couch': 2125, 'populated': 6757, 'grade': 3978, 'desperate': 2546, 'effeminate': 2959, 'husbands': 4452, 'suppose': 8733, 'kicks': 5001, 'awakening': 771, 'social': 8265, 'spoke': 8401, 'racial': 7090, 'vietnam': 9538, 'sexual': 7950, 'fabric': 3318, 'news': 6071, 'largely': 5117, 'succeeded': 8664, 'followed': 3611, 'follows': 3614, 'equal': 3124, 'basis': 862, 'dedicated': 2415, 'admittedly': 279, 'consideration': 2004, 'century': 1524, 'footage': 3624, 'mixed': 5806, 'color': 1834, 'fiction': 3460, 'clips': 1760, 'situations': 8155, 'sided': 8086, '1st': 90, '2003': 96, 'drab': 2784, 'un': 9318, 'spectacular': 8360, 'ended': 3050, 'thru': 9036, 'sequels': 7906, 'etc': 3158, 'renting': 7361, 'buying': 1338, 'fare': 3374, 'cruella': 2249, 'prison': 6901, 'busy': 1327, 'helping': 4250, 'homeless': 4349, 'dogs': 2739, 'clock': 1763, 'hypnotic': 4460, 'cure': 2273, 'reversed': 7458, 'determined': 2569, 'coat': 1795, 'wanted': 9648, 'glenn': 3908, 'feels': 3430, 'repeat': 7363, 'previous': 6880, 'changed': 1550, 'ken': 4984, '17': 14, 'screwed': 7805, 'phantasm': 6594, '1988': 76, 'gory': 3960, 'creator': 2191, '1994': 83, 'originality': 6311, 'attempts': 718, 'tiresome': 9074, 'disappointing': 2654, 'comparison': 1898, 'spoilers': 8399, 'introduced': 4745, 'mysterious': 5970, 'sentinel': 7900, 'brain': 1179, 'sucking': 8675, 'flying': 3596, 'balls': 828, 'annoying': 516, 'kid': 5002, 'swinging': 8794, 'crew': 2204, 'qualities': 7058, 'pony': 6745, 'guitar': 4074, 'talks': 8842, 'loose': 5359, 'baldwin': 824, 'replaced': 7370, 'james': 4828, 'opinion': 6283, 'disappointment': 2655, 'acceptable': 188, 'expectations': 3250, 'foremost': 3637, 'weren': 9744, 'brando': 1185, 'damon': 2318, 'irony': 4782, 'salvation': 7686, 'office': 6236, 'simmons': 8114, 'sewer': 7946, 'weak': 9706, 'power': 6807, 'filled': 3484, 'electricity': 2983, 'restaurant': 7424, 'pull': 7015, 'vocal': 9593, 'vivian': 9590, 'proceedings': 6911, 'obvious': 6203, 'weakest': 9708, 'terms': 8922, 'shoe': 8037, 'nightclub': 6086, 'stage': 8435, 'hadn': 4102, 'whenever': 9764, 'reminded': 7341, 'cash': 1465, 'square': 8424, 'phony': 6610, 'drew': 2820, 'sequence': 7907, '1955': 44, 'musicals': 5950, 'changing': 1552, 'location': 5330, 'photography': 6616, '1949': 39, 'stuff': 8620, 'taking': 8833, 'dolls': 2744, 'bound': 1154, 'cute': 2290, 'legal': 5190, 'regard': 7272, 'les': 5214, 'certain': 1527, 'major': 5470, 'complaint': 1915, 'bet': 977, 'wedding': 9723, 'added': 254, 'marion': 5527, 'waiting': 9619, 'upstairs': 9439, 'suddenly': 8678, 'switch': 8796, 'convey': 2069, 'cross': 2235, 'extremely': 3310, 'talented': 8836, 'spike': 8380, 'franklin': 3695, 'dukes': 2866, 'host': 4395, 'wayans': 9702, 'brothers': 1253, 'colour': 1838, 'stupidity': 8632, 'humour': 4434, 'gags': 3778, 'toilet': 9091, 'operating': 6281, 'baby': 793, 'accepted': 190, 'months': 5855, 'shadow': 7960, 'foster': 3671, 'master': 5572, 'stupidest': 8631, 'planet': 6672, 'earth': 2914, 'stolen': 8542, 'purse': 7038, 'pursue': 7039, 'surrounded': 8755, 'morons': 5881, 'bunny': 1301, 'remotely': 7348, 'clue': 1783, 'prior': 6900, 'bat': 865, 'awards': 775, 'mans': 5511, 'guilt': 4070, 'limitations': 5273, 'clever': 1738, 'relying': 7323, 'devotion': 2587, '1000': 5, 'shorts': 8053, 'horrors': 4391, 'business': 1323, 'insulting': 4692, 'criticism': 2224, 'wondering': 9871, 'reviewer': 7461, 'desired': 2543, 'bashing': 857, 'satisfy': 7724, 'mindless': 5746, 'empty': 3037, 'stick': 8524, 'message': 5696, 'assault': 674, 'draws': 2804, 'spirit': 8386, 'curtis': 2284, 'party': 6472, 'laughed': 5138, 'hurt': 4448, 'naturally': 6008, 'pie': 6634, 'tasteless': 8864, 'hole': 4337, 'purpose': 7036, 'nudity': 6168, 'glad': 3897, 'silly': 8106, 'ron': 7584, 'melinda': 5657, 'engaged': 3065, 'dating': 2360, 'scared': 7749, 'weekend': 9726, 'miami': 5712, 'marriage': 5541, 'accomplished': 204, 'likable': 5260, 'seth': 7931, 'nerves': 6054, 'wanna': 9645, 'wild': 9803, 'tears': 8883, 'mccoy': 5613, 'spock': 8395, 'trapped': 9202, 'ice': 4464, 'capt': 1411, 'kirk': 5030, 'colonial': 1832, 'former': 3654, 'pair': 6410, 'freezing': 3711, 'third': 8995, 'sexy': 7953, 'hartley': 4176, 'spends': 8374, 'feeling': 3428, 'attraction': 732, 'throwing': 9033, 'caution': 1494, 'leaving': 5182, 'grasp': 3999, 'stand': 8451, 'hilt': 4297, 'knocking': 5048, 'installment': 4680, 'captain': 1412, 'shatner': 7991, 'responsible': 7422, 'sending': 7881, 'trio': 9245, 'modern': 5823, 'fit': 3534, 'harder': 4155, 'experienced': 3258, 'risks': 7520, 'producers': 6918, 'cringe': 2212, 'awe': 779, 'simplicity': 8118, 'terrifying': 8928, 'laurie': 5149, 'jamie': 4830, 'madman': 5445, 'escaping': 3143, 'mental': 5675, 'institution': 4688, 'brutally': 1263, 'murdering': 5939, 'myers': 5964, 'teenage': 8895, 'population': 6758, 'brainless': 1180, 'slasher': 8186, 'frequently': 3714, 'splatter': 8392, 'theaters': 8959, '1970s': 57, 'rightfully': 7503, 'downright': 2778, 'entries': 3113, 'teen': 8894, 'argue': 606, 'tongue': 9110, 'cheek': 1599, 'fail': 3335, 'carpenter': 1447, 'todays': 9086, 'sadistic': 7664, 'scares': 7750, 'skill': 8164, 'seal': 7817, 'die': 2604, 'idiots': 4482, 'mistake': 5794, 'swallow': 8781, 'ridiculously': 7497, 'elements': 2987, 'inventive': 4753, 'murders': 5941, 'pieces': 6636, 'order': 6299, 'twice': 9293, 'primitive': 6891, 'repeated': 7364, 'lesser': 5219, 'conflicted': 1971, 'exception': 3214, 'shape': 7981, 'asking': 663, 'pulls': 7018, 'chilling': 1634, 'brilliance': 1226, 'supports': 8732, 'lure': 5419, 'freedom': 3708, 'advantage': 293, 'recognize': 7227, 'fear': 3413, 'luckily': 5405, 'intimacy': 4736, 'gear': 3820, 'stops': 8553, 'flawed': 3557, 'immensely': 4525, 'warned': 9663, 'scare': 7746, 'redundant': 7250, 'courtney': 2147, 'escapes': 3142, 'desert': 2529, 'raped': 7141, 'stalked': 8444, 'appears': 573, 'craig': 2168, 'attempting': 717, 'mickey': 5719, 'rourke': 7610, 'imitation': 4520, 'supposedly': 8735, 'protect': 6980, 'serve': 7922, 'meanwhile': 5633, 'logic': 5337, 'flies': 3571, 'returns': 7445, 'unanswered': 9320, 'questions': 7071, 'saved': 7731, 'baker': 818, 'insignificant': 4668, 'disc': 2661, 'necessarily': 6024, 'depending': 2502, 'smaller': 8225, 'forgive': 3645, 'imaginative': 4513, 'alan': 371, 'arkin': 615, 'claire': 1710, 'unrealistic': 9412, 'personally': 6572, 'readily': 7181, 'helped': 4248, 'engage': 3064, 'gratuitous': 4003, 'adult': 287, 'language': 5111, 'swear': 8783, 'correctly': 2112, 'cameos': 1367, 'reflects': 7265, 'chinese': 1637, 'underground': 9342, 'bands': 831, 'current': 2278, 'culture': 2268, 'succeeding': 8665, 'pulling': 7017, 'failing': 3337, 'transfer': 9185, 'courtroom': 2148, 'abraham': 165, 'lincoln': 5277, 'henry': 4257, 'fonda': 3616, 'trial': 9231, 'walks': 9630, 'statue': 8488, 'acted': 229, 'spark': 8348, 'suspect': 8767, 'melodrama': 5659, 'starring': 8469, 'ingrid': 4639, 'bergman': 967, 'meandering': 5625, 'forwarding': 3670, 'fall': 3352, 'asleep': 665, 'whom': 9785, 'crush': 2253, 'motif': 5893, 'bicycle': 996, 'thief': 8986, 'extended': 3301, 'metaphor': 5703, 'juvenile': 4948, 'discipline': 2663, 'accused': 212, 'societal': 8267, 'confines': 1968, 'sorry': 8318, 'reviewers': 7462, 'stated': 8480, 'vintage': 9560, '20th': 104, 'fox': 3678, 'basic': 858, 'ingredients': 4638, 'determination': 2567, 'comedians': 1854, 'situation': 8154, 'essence': 3147, 'eternal': 3159, 'faced': 3321, 'namely': 5987, 'related': 7294, 'stress': 8580, 'checked': 1596, 'staying': 8492, 'plausible': 6682, 'circumstances': 1696, 'awhile': 785, 'relate': 7293, 'caused': 1491, 'stan': 8449, 'ollie': 6258, 'universal': 9393, 'appeal': 565, 'presented': 6857, 'delightfully': 2454, 'slapstick': 8184, 'roach': 7533, 'studios': 8617, 'exclusively': 3226, 'hurry': 4447, 'finish': 3510, 'stayed': 8491, 'continued': 2039, 'catholic': 1486, 'church': 1679, 'sin': 8124, 'individual': 4602, 'ritual': 7524, 'sins': 8141, 'dying': 2891, 'often': 6244, 'individuals': 4603, 'thereby': 8979, 'denying': 2494, 'entrance': 3112, 'redemption': 7246, 'overt': 6368, 'wander': 9641, 'combines': 1848, 'religious': 7319, 'anti': 528, 'files': 3482, 'thorn': 9004, 'birds': 1017, 'alex': 384, 'ledger': 5185, 'priest': 6886, 'demon': 2473, 'fighting': 3476, 'priests': 6887, 'mentor': 5682, 'peter': 6586, 'sends': 7882, 'investigate': 4755, 'underworld': 9357, 'ominous': 6263, 'demonic': 2474, 'claiming': 1708, 'surviving': 8762, 'knight': 5042, 'intrigue': 4740, 'occasional': 6206, 'bursts': 1314, 'despair': 2545, 'displayed': 2692, 'notably': 6139, 'forth': 3662, 'arc': 597, 'containing': 2024, 'herrings': 4271, 'gaps': 3798, 'narrative': 5993, 'confusing': 1980, 'structure': 8602, 'coupled': 2140, 'clear': 1735, 'antagonist': 525, 'blatantly': 1049, 'background': 802, 'eating': 2924, 'explained': 3269, 'dry': 2848, 'exposition': 3292, 'combine': 1846, '80': 141, 'subtle': 8656, 'organic': 6304, 'torn': 9130, 'lisa': 5295, 'exotic': 3246, 'remains': 7329, 'watchable': 9684, 'sensibilities': 7888, 'angry': 493, 'functions': 3750, 'sheer': 8002, 'prevent': 6876, 'critical': 2223, 'commercial': 1875, 'amounts': 459, 'recommended': 7231, 'memory': 5670, 'billed': 1006, 'error': 3138, 'attracted': 731, 'sensitivity': 7892, 'exudes': 3312, 'cheers': 1603, 'reads': 7183, 'proves': 6990, 'darker': 2346, 'agreed': 341, 'straightforward': 8562, 'nicole': 6082, 'kidman': 5005, 'vehicle': 9498, 'wrapped': 9914, 'closing': 1774, 'chaplin': 1558, 'implausible': 4534, 'ebert': 2927, 'screwball': 7804, 'ready': 7184, '1930s': 20, 'weird': 9730, 'birthday': 1019, 'killer': 5012, 'reign': 7287, '2007': 100, 'adam': 246, 'sandler': 7698, 'cheadle': 1588, 'tyler': 9302, 'sutherland': 8779, 'dillon': 2622, 'jonathan': 4903, 'banks': 834, 'allen': 404, 'paula': 6503, 'affecting': 309, 'thoroughly': 9005, '11': 6, 'united': 9392, 'college': 1827, 'roommate': 7589, 'continuing': 2041, 'date': 2357, 'wealth': 9711, 'happiness': 4148, 'ally': 413, 'offerings': 6234, 'genuine': 3848, 'week': 9725, 'solution': 8283, 'zhang': 9988, 'purple': 7035, 'commented': 1872, 'significant': 8100, 'portions': 6766, 'endless': 3053, 'smoking': 8240, 'cigarettes': 1682, 'sitting': 8153, 'shifts': 8018, 'beforehand': 915, 'understanding': 9349, 'smiles': 8235, 'participants': 6461, 'apart': 551, 'angel': 483, 'sent': 7894, 'mum': 5929, 'amused': 463, 'unfunny': 9375, 'corky': 2099, 'romano': 7578, 'unlikable': 9399, 'jokes': 4898, 'mannered': 5507, 'vet': 9519, 'tries': 9242, 'clumsy': 1787, 'fbi': 3412, 'destroy': 2555, 'trace': 9160, 'believes': 942, 'duty': 2884, 'mayhem': 5606, 'ensue': 3089, 'settle': 7935, 'chris': 1662, 'kattan': 4967, 'solely': 8279, 'slap': 8182, 'snl': 8254, 'tone': 9107, 'rely': 7322, 'telling': 8902, 'mafia': 5450, 'awkward': 786, 'plenty': 6699, 'forgettable': 3642, 'screenwriters': 7802, 'comedic': 1855, 'penn': 6535, 'falk': 3351, 'car': 1419, 'latest': 5132, 'react': 7175, 'according': 206, 'wondered': 9868, 'warhols': 9658, 'bjm': 1031, 'exploitation': 3278, 'max': 5602, 'total': 9138, 'portrait': 6768, 'genius': 3841, 'ourselves': 6332, 'rented': 7360, '90': 144, 'modesty': 5825, 'alexandra': 386, 'raymond': 7166, 'cruz': 2255, 'garcia': 3802, 'tarantino': 8853, 'interested': 4719, 'willie': 9811, 'drop': 2834, 'wicker': 9791, 'ask': 660, 'warn': 9662, 'sarcasm': 7710, 'cage': 1350, 'island': 4794, 'answers': 524, 'holes': 4338, 'fill': 3483, 'library': 5240, 'shady': 7962, 'outline': 6344, 'delightful': 2453, 'ex': 3199, 'via': 9523, 'wrongly': 9931, 'rolling': 7571, 'lake': 5094, 'district': 2713, 'hills': 4296, 'sheep': 8001, 'bunch': 1299, 'amateur': 435, 'chases': 1583, 'skilled': 8165, 'hours': 4404, 'layers': 5158, 'east': 2918, 'english': 3071, 'shameful': 7975, 'monty': 5857, 'sally': 7681, 'field': 3464, 'andrew': 479, 'honeymoon': 4360, 'vegas': 9497, 'soap': 8261, 'wall': 9631, 'beats': 894, 'daytime': 2373, '1991': 80, 'duchovny': 2854, 'unfair': 9366, 'addicted': 256, 'struck': 8601, 'accident': 195, 'private': 6904, 'millionaire': 5741, 'blossom': 1077, 'angelina': 486, 'jolie': 4900, 'gangsters': 3795, 'immersed': 4526, 'credible': 2196, 'detract': 2570, 'cowboy': 2159, 'hoffman': 4332, 'daniel': 2336, 'lewis': 5233, 'butcher': 1330, 'gangs': 3793, 'comparable': 1894, 'ratso': 7159, 'raises': 7112, 'levels': 5231, 'buck': 1270, 'naive': 5983, 'altogether': 430, 'teaches': 8877, 'importantly': 4541, 'gritty': 4039, 'clearly': 1736, 'possession': 6787, 'insight': 4665, 'accept': 187, 'abuse': 180, 'fully': 3747, 'gosh': 3961, 'inner': 4652, 'justify': 4946, 'eli': 2992, 'helpful': 4249, 'led': 5184, 'evident': 3190, 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5609, 'forever': 3639, 'simpsons': 8122, 'remain': 7325, 'tremendously': 9227, 'outrageously': 6347, 'dude': 2857, 'heroes': 4266, 'walken': 9627, 'labeled': 5079, 'guilty': 4071, 'convince': 2076, 'intellectual': 4699, 'preposterous': 6852, 'non': 6114, 'clichéd': 1744, 'nonsensical': 6119, 'staged': 8436, 'drawings': 2802, 'delirious': 2455, 'pow': 6805, 'soldier': 8276, 'symbol': 8807, 'debt': 2395, 'rebel': 7210, 'revolution': 7467, 'corrupt': 2115, 'president': 6861, 'columbia': 1840, 'el': 2975, 'balcony': 822, 'travels': 9213, 'financial': 3501, 'assistance': 680, 'fed': 3422, 'injustice': 4650, 'miserable': 5777, 'plane': 6670, 'gigantic': 3878, 'fool': 3619, 'user': 9451, 'add': 253, 'senseless': 7886, 'needless': 6032, 'heroic': 4267, 'goal': 3924, 'mission': 5792, 'squad': 8423, '100': 4, 'coherent': 1807, 'flamboyant': 3543, 'exact': 3200, 'outrageous': 6346, 'national': 6003, 'apocalypse': 558, 'explosions': 3288, 'soundtrack': 8329, 'joan': 4880, 'sings': 8136, 'arch': 598, '60s': 133, 'spell': 8367, 'twisted': 9298, 'evokes': 3194, 'teacher': 8875, 'linked': 5287, 'antonioni': 535, 'twelve': 9290, 'print': 6898, 'projected': 6946, 'correct': 2111, 'size': 8159, 'immense': 4524, 'restored': 7426, 'cultural': 2267, 'agency': 331, 'importance': 4539, 'keeping': 4976, 'gasp': 3812, 'valley': 9469, 'thousand': 9011, 'shock': 8030, 'intentionally': 4712, 'wake': 9622, 'awareness': 777, 'entirely': 3108, 'astonishing': 694, '80s': 142, 'begun': 924, 'affection': 310, 'olivia': 6256, 'leonard': 5212, 'romeo': 7581, 'juliet': 4930, 'daylight': 2371, 'enjoyment': 3082, 'shoulder': 8058, 'padded': 6395, 'haired': 4107, 'hippie': 4308, 'force': 3630, 'realised': 7188, 'inside': 4664, 'answered': 522, 'uh': 9310, 'secretly': 7839, 'thrilled': 9022, 'march': 5519, 'undoubtedly': 9358, 'constructed': 2017, 'environment': 3115, 'glimpse': 3909, 'newspaper': 6072, 'photo': 6611, 'mysteriously': 5971, 'antics': 532, 'alice': 390, 'peace': 6517, 'thinks': 8993, 'moron': 5879, 'advise': 301, 'hits': 4324, 'acid': 222, 'thrill': 9021, 'wasting': 9682, 'requires': 7392, 'info': 4629, 'defend': 2427, 'paper': 6433, 'ringing': 7507, 'clouds': 1779, 'sunny': 8710, 'lion': 5289, 'forty': 3667, 'fault': 3400, 'stiff': 8527, 'ultra': 9315, 'unlike': 9400, 'clockwork': 1764, 'orange': 6296, 'sum': 8700, 'straw': 8571, 'pete': 6585, 'walker': 9628, 'desire': 2542, 'bedroom': 908, 'pitiful': 6654, 'misogynistic': 5786, 'merely': 5688, 'depiction': 2507, 'leg': 5188, 'par': 6436, 'makers': 5474, 'daring': 2344, 'unpleasant': 9408, 'aim': 351, 'latin': 5133, 'removed': 7350, 'likewise': 5266, 'remove': 7349, 'noble': 6102, 'impulse': 4556, 'ealing': 2902, 'carol': 1445, 'reed': 7251, 'graham': 3982, 'greene': 4021, 'fallen': 3353, 'idol': 4484, 'sublime': 8644, 'powell': 6806, 'sidney': 8090, 'lumet': 5413, 'hopkins': 4378, 'glory': 3917, 'hateful': 4186, 'celluloid': 1512, 'bette': 982, 'davis': 2367, 'flop': 3583, 'variation': 9483, 'hilariously': 4293, 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'widely': 9793, 'manages': 5492, 'explore': 3283, 'vienna': 9537, 'offer': 6231, 'infatuated': 4618, 'sunrise': 8711, 'breath': 1202, 'decline': 2413, 'charisma': 1571, 'inspired': 4678, 'canadian': 1381, 'available': 761, 'region': 7278, 'uk': 9311, '13': 8, 'seasons': 7826, 'amazon': 440, 'shepherd': 8012, 'brick': 1216, 'harris': 4169, 'fred': 3705, 'priceless': 6884, 'godfather': 3928, 'spoof': 8404, 'kinds': 5023, 'stock': 8539, 'uneven': 9362, 'humble': 4430, 'wretched': 9921, 'holy': 4346, 'law': 5151, 'conflict': 1970, 'sub': 8639, 'omen': 6262, 'jumped': 4933, 'beware': 988, 'fooled': 3620, 'widescreen': 9795, 'ratio': 7156, 'generally': 3832, 'producer': 6917, 'hopelessly': 4375, 'travesty': 9214, 'masquerading': 5566, 'convinced': 2077, 'adapted': 251, 'rapist': 7145, 'terrified': 8927, 'roommates': 7590, 'tables': 8820, 'proved': 6989, 'arrested': 631, 'confession': 1964, 'claustrophobic': 1728, 'farrah': 3379, 'fawcett': 3410, 'awarded': 774, 'victim': 9528, 'refuses': 7270, 'critics': 2228, 'russo': 7649, 'slimy': 8212, 'challenge': 1536, 'assumed': 687, 'diana': 2594, 'stuffed': 8621, 'fireplace': 3521, 'faint': 3341, 'grabs': 3974, 'funeral': 3754, 'material': 5585, 'platoon': 6681, 'singers': 8132, 'flowers': 3589, 'admirer': 274, 'clichés': 1745, 'jail': 4826, 'religion': 7318, 'sunk': 8709, 'granddaughter': 3988, 'leslie': 5217, 'caron': 1446, 'notes': 6143, 'button': 1335, 'olympia': 6260, 'dukakis': 2864, 'grabbing': 3973, 'scotland': 7786, 'converted': 2068, 'reunited': 7448, 'youngsters': 9969, 'intend': 4704, 'jason': 4841, 'rachel': 7089, 'ward': 9653, 'heat': 4226, 'footsteps': 3626, 'flashback': 3548, 'weirdness': 9731, 'wars': 9672, 'tax': 8869, 'lucas': 5402, 'christensen': 1664, '60': 132, 'fights': 3477, 'edge': 2937, 'fleeting': 3563, 'jar': 4838, 'picks': 6630, 'jedi': 4851, 'overlong': 6361, 'husband': 4451, 'tends': 8917, 'occasionally': 6207, 'videos': 9535, 'redford': 7247, 'perception': 6545, 'montana': 5853, 'upbringing': 9430, 'calling': 1361, 'critic': 2222, 'disagree': 2646, 'contemplate': 2026, 'rhythm': 7479, 'fisher': 3531, 'boxer': 1163, 'brad': 1175, 'pitt': 6656, 'alcoholism': 381, 'applies': 578, 'burns': 1310, 'worms': 9895, 'bait': 816, 'wait': 9617, 'table': 8819, 'plate': 6679, 'jessie': 4866, 'emily': 3018, 'chicago': 1621, 'narrator': 5994, 'comparing': 1897, 'nominated': 6111, 'visionary': 9577, 'deserves': 2535, 'technology': 8890, 'magnificently': 5459, 'ultimate': 9312, 'curse': 2281, 'attending': 723, 'toronto': 9132, 'messed': 5698, 'fido': 3463, 'distribution': 2711, 'shaun': 7993, 'currie': 2280, 'themed': 8967, 'press': 6863, '50s': 130, 'infamous': 4617, 'pulp': 7019, 'carrie': 1451, 'moss': 5886, 'dylan': 2893, 'blake': 1039, 'nelson': 6046, 'testament': 8938, 'explores': 3285, 'zombies': 9994, 'servants': 7921, 'servant': 7920, 'butler': 1332, 'labor': 5080, 'pet': 6584, 'acts': 240, 'possibilities': 6788, 'classy': 1725, 'bitter': 1028, 'jumps': 4935, 'beaten': 891, 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'grabbed': 3972, 'teddy': 8892, 'superman': 8722, 'mighty': 5727, 'rambo': 7118, 'matrix': 5588, 'jackie': 4818, 'chan': 1544, 'jet': 4868, 'li': 5235, 'pointless': 6720, 'lethal': 5225, 'mask': 5562, 'martial': 5549, 'arts': 649, 'supreme': 8737, 'lose': 5368, 'amazingly': 439, 'choreographed': 1656, 'marvel': 5555, 'kick': 4998, 'department': 2499, 'flock': 3579, 'danes': 2330, 'synopsis': 8816, 'posted': 6793, 'online': 6269, 'trite': 9250, 'nauseating': 6012, 'wishes': 9842, 'castle': 1473, 'sky': 8177, 'miyazaki': 5809, 'magical': 5455, 'avoided': 766, 'costs': 2122, 'translation': 9196, 'viewed': 9540, 'enthusiasts': 3106, 'varied': 9485, 'keen': 4973, 'steaming': 8500, 'rousing': 7611, 'sir': 8142, 'risk': 7519, 'penny': 6537, 'association': 684, 'christian': 1665, 'slater': 8188, 'admits': 277, 'signed': 8098, 'pity': 6657, 'hapless': 4141, 'stumbles': 8624, 'indulgence': 4607, 'animals': 498, 'lavish': 5150, 'circumstance': 1695, 'walt': 9637, 'identical': 4474, 'authority': 755, 'atlantis': 702, 'whacked': 9754, 'till': 9056, 'absolute': 171, 'hammy': 4120, 'deliberate': 2446, 'stealing': 8496, 'stopped': 8551, 'muted': 5961, 'pleased': 6695, 'media': 5640, 'worthy': 9906, 'oliver': 6255, 'stone': 8545, 'born': 1138, 'machine': 5436, 'majority': 5471, 'larger': 5118, 'christ': 1663, 'overwhelming': 6373, 'produce': 6915, 'antonio': 534, 'eerie': 2953, 'chiller': 1633, 'vibe': 9524, 'journalist': 4910, 'interview': 4732, 'visiting': 9581, 'poe': 6711, 'bets': 981, 'spend': 8372, 'accepting': 191, 'locked': 5334, 'crypt': 2258, 'unbearable': 9324, 'steele': 8503, 'sinister': 8137, 'captivating': 1414, 'smell': 8233, 'cinematographic': 1690, 'texture': 8945, 'plastic': 6678, 'perspective': 6575, 'notion': 6151, 'grandmother': 3991, 'cooking': 2084, 'authentic': 751, 'bottom': 1151, 'description': 2528, 'cbs': 1497, 'versatile': 9513, 'guardian': 4061, 'kathleen': 4964, 'divorced': 2724, 'nurse': 6176, 'hospital': 4394, 'er': 3128, 'maintains': 5468, 'shut': 8077, '000': 1, 'briefly': 1223, 'lifted': 5250, 'spots': 8413, 'noah': 6100, 'bravery': 1190, 'performed': 6552, 'firefighter': 3519, 'hank': 4136, 'russ': 7644, 'hasn': 4182, 'quietly': 7075, 'slip': 8213, 'explanation': 3272, '50': 128, 'claus': 1727, 'suit': 8693, 'floating': 3578, 'pops': 6754, 'tie': 9048, 'com': 1842, 'ireland': 4775, 'ancient': 473, 'practices': 6815, 'repeatedly': 7365, 'dangers': 2334, 'path': 6489, 'irish': 4778, 'courtesy': 2146, 'cannibals': 1392, 'bean': 883, 'clan': 1711, 'settled': 7936, 'automatically': 760, 'tons': 9113, 'breed': 1208, 'ginger': 3886, 'lynn': 5429, 'marvellous': 5556, 'brutal': 1261, 'slaughter': 8189, 'canvas': 1397, 'enhanced': 3075, 'hottie': 4401, 'dragged': 2787, 'spit': 8390, 'downhill': 2777, 'somethings': 8294, 'begging': 919, 'cannibal': 1391, 'subjected': 8642, 'fair': 3342, 'form': 3650, 'murderous': 5940, 'gary': 3810, 'simon': 8115, 'conventions': 2065, 'knife': 5041, 'shower': 8069, 'gillian': 3883, 'leigh': 5198, 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'witnessed': 9853, 'glance': 3901, 'spiritual': 8389, 'preserved': 6860, 'design': 2538, 'resembles': 7399, 'cow': 2156, 'chicken': 1623, 'segment': 7863, 'minded': 5745, 'fort': 3661, 'grounds': 4045, 'connections': 1986, 'tear': 8882, 'mirrors': 5773, 'pacino': 6389, 'speech': 8362, 'coffin': 1804, 'remarkable': 7333, 'dialogues': 2592, 'scripts': 7809, 'interestingly': 4721, 'oriented': 6308, 'fabulous': 3319, 'sirk': 8143, 'filmmaking': 3493, 'hudson': 4416, 'dorothy': 2765, 'malone': 5483, 'stack': 8432, 'lauren': 5147, 'bacall': 795, 'brilliantly': 1228, 'sharon': 7989, 'guru': 4083, 'instinct': 4686, 'biting': 1025, 'trashy': 9205, 'dazzling': 2374, 'smooth': 8241, 'montage': 5851, 'unforgettable': 9372, 'scratching': 7790, 'censors': 1515, 'regarded': 7273, 'chore': 1655, 'greatly': 4013, 'creations': 2188, 'craft': 2166, 'apprentice': 583, 'difficulties': 2614, 'tricks': 9238, 'madness': 5446, 'nazi': 6014, 'fewer': 3454, 'caught': 1489, 'screening': 7797, 'develops': 2579, 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729, 'foundation': 3675, 'sparks': 8349, 'flare': 3546, 'ignorance': 4487, 'delivery': 2461, 'farce': 3373, 'originally': 6312, 'irene': 4776, 'dunne': 2874, 'funnier': 3756, 'blend': 1054, 'palette': 6421, 'foil': 3606, 'shannon': 7979, 'assistant': 681, 'lovable': 5383, 'maid': 5461, 'pairing': 6412, 'drake': 2793, 'tomorrow': 9105, 'futuristic': 3768, 'trailers': 9176, 'extras': 3308, 'dutch': 2882, 'widow': 9797, 'spider': 8377, 'prey': 6882, 'web': 9721, 'gerard': 3854, 'reve': 7449, 'centered': 1518, 'morbid': 5869, 'invited': 4762, 'guest': 4066, 'glimpses': 3910, 'insanity': 4660, 'flood': 3580, 'accepts': 192, 'wealthy': 9712, 'figured': 3479, 'cg': 1529, 'jude': 4917, 'gwyneth': 4089, 'paltrow': 6425, 'infinitely': 4624, 'racing': 7091, 'indiana': 4595, 'esquire': 3146, 'term': 8920, 'dashing': 2355, 'melting': 5663, 'perkins': 6561, 'nerve': 6053, 'grating': 4002, 'whining': 9774, 'sarcastic': 7711, 'heroine': 4269, 'phantom': 6595, 'swanson': 8782, 'steady': 8494, 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3615, 'obscurity': 6192, 'sudden': 8677, 'massive': 5571, 'boston': 1143, 'ruins': 7628, 'terry': 8935, 'verge': 9508, 'territory': 8929, 'document': 2731, 'dinosaurs': 2630, 'generations': 3836, 'informative': 4632, 'rush': 7642, 'demanding': 2466, 'absent': 170, 'twilight': 9294, 'unoriginal': 9407, 'frontier': 3732, 'staff': 8434, 'killings': 5015, 'salt': 7684, 'pepper': 6540, 'sums': 8704, 'irrelevant': 4784, 'banned': 835, 'daft': 2305, 'weapon': 9713, 'shrek': 8075, '3d': 122, 'bug': 1283, 'iq': 4770, 'im': 4506, 'gonna': 3944, 'recipe': 7223, 'joking': 4899, 'likeable': 5262, 'pathos': 6491, 'cookie': 2083, 'cutter': 2292, 'mock': 5815, 'michelle': 5717, 'rodriguez': 7561, 'mtv': 5923, 'easier': 2916, 'deceased': 2400, '13th': 9, 'morgue': 5875, 'popped': 6752, 'jacket': 4817, 'screaming': 7793, 'oddity': 6220, 'trance': 9183, 'frame': 3683, 'lean': 5170, 'knack': 5038, 'affect': 307, 'lou': 5378, 'martha': 5548, 'christianity': 1666, '700': 137, 'reliable': 7315, 'abc': 153, 'pbs': 6515, 'programs': 6938, 'operation': 6282, 'blessing': 1058, 'medical': 5641, 'poverty': 6804, 'stricken': 8584, 'communities': 1888, 'reaching': 7174, 'seduce': 7845, 'hilton': 4298, 'stoned': 8546, 'tea': 8873, 'hers': 4272, 'bull': 1291, 'incapable': 4564, 'raising': 7113, 'bros': 1250, '1946': 37, 'mature': 5595, 'brains': 1181, 'bothering': 1148, 'kalifornia': 4952, 'snatch': 8248, 'photographs': 6615, 'ravishing': 7163, 'walls': 9634, 'express': 3294, 'fart': 3381, 'attached': 709, 'fish': 3529, 'frost': 3733, 'wright': 9922, 'consequences': 1998, 'rom': 7573, 'ted': 8891, 'bogus': 1099, 'entertains': 3102, 'geisha': 3825, 'samurai': 7694, 'surroundings': 8757, 'dances': 2326, 'screw': 7803, 'sibling': 8079, 'rivalry': 7526, 'startling': 8476, 'aids': 349, 'irresponsible': 4786, 'responsibility': 7421, 'addiction': 257, 'tender': 8915, 'competent': 1906, 'innuendo': 4656, 'crisis': 2216, 'sob': 8262, 'ably': 158, 'establish': 3150, 'melissa': 5658, 'owned': 6380, 'mountain': 5903, 'mars': 5545, 'alright': 421, 'shine': 8020, 'duration': 2877, 'revolves': 7470, 'cheaply': 1591, 'neurotic': 6060, 'gloria': 3914, 'greats': 4015, 'downey': 2775, 'kathy': 4966, 'elevate': 2989, 'predictably': 6835, 'achieve': 215, 'mel': 5654, 'anxiety': 539, '1977': 64, 'exploitative': 3279, 'versus': 9516, 'payoff': 6512, 'thick': 8985, 'nicholas': 6077, 'bronte': 1245, 'dalton': 2311, 'rochester': 7551, 'possesses': 6786, 'portrays': 6774, 'calls': 1362, 'suffers': 8683, 'bully': 1295, 'perceived': 6543, 'zelah': 9983, 'clarke': 1716, '18': 15, 'attributes': 735, 'temper': 8905, 'aims': 355, 'household': 4406, 'tempered': 8906, 'theirs': 8963, 'presumed': 6869, 'miracle': 5767, 'poetic': 6714, 'gypsy': 4092, 'eyre': 3316, 'significance': 8099, 'equipment': 3126, 'text': 8943, 'remembering': 7338, 'symbols': 8810, 'jewelry': 4871, 'marries': 5543, 'movement': 5912, 'boxing': 1165, 'object': 6183, 'desires': 2544, 'budgets': 1278, 'keys': 4994, 'shorter': 8051, 'cameras': 1370, 'casted': 1471, 'roth': 7603, 'kyle': 5075, 'englund': 3072, 'winston': 9831, 'scorsese': 7785, 'dallas': 2310, 'superstar': 8725, 'madonna': 5447, 'francisco': 3690, 'inch': 4567, 'annoyed': 515, 'tenant': 8911, 'tara': 8852, 'fitzgerald': 3537, 'letting': 5229, 'hairdo': 4106, 'cruelty': 2250, 'springer': 8420, 'extent': 3303, 'subtly': 8659, 'skinny': 8170, 'shell': 8006, 'formulaic': 3658, 'manchu': 5494, 'assassins': 673, 'wink': 9826, 'fantasies': 3369, 'secluded': 7832, 'awakens': 772, 'clueless': 1784, 'franco': 3691, 'abandon': 150, 'admitted': 278, 'admired': 273, 'experiencing': 3260, 'poet': 6713, 'corman': 2101, 'bucket': 1271, 'posh': 6779, 'unusually': 9424, 'embrace': 3014, 'represented': 7382, 'larry': 5120, 'sanders': 7697, 'amusement': 464, 'nt': 6162, 'townsfolk': 9155, 'preacher': 6823, 'identities': 4477, 'pretending': 6871, 'deaf': 2379, 'paperhouse': 6434, 'anyhow': 543, 'adding': 258, 'increasingly': 4587, 'ongoing': 6268, 'blames': 1042, 'disastrous': 2659, 'pals': 6424, 'elm': 3001, 'ish': 4793, 'handy': 4132, 'conclusions': 1956, 'charlotte': 1576, 'burke': 1306, 'definite': 2435, 'worried': 9897, 'clone': 1765, 'twins': 9296, 'designer': 2540, 'pause': 6505, 'snake': 8245, 'fx': 3770, 'loss': 5373, 'distract': 2704, 'laundry': 5144, 'concerning': 1951, 'pond': 6744, 'cushing': 2286, 'chloe': 1639, 'reid': 7286, 'maher': 5460, 'politically': 6738, 'incorrect': 4584, 'valid': 9468, 'argument': 608, 'experts': 3267, 'scientists': 7776, 'fields': 3465, 'professionals': 6928, 'sources': 8333, 'education': 2949, 'refers': 7261, 'evidence': 3189, 'herd': 4261, 'exceptions': 3217, 'norm': 6125, 'laurence': 5148, 'christians': 1667, 'inaccuracies': 4559, 'questioning': 7070, 'deck': 2412, 'relates': 7295, 'october': 6217, 'mining': 5755, 'grows': 4051, 'miner': 5750, 'stares': 8464, 'passes': 6479, 'occupation': 6210, 'test': 8937, 'rockets': 7555, 'blow': 1078, 'fence': 3443, 'dern': 2520, 'judges': 4921, 'motives': 5900, 'bent': 964, 'recycled': 7242, 'stole': 8541, '1997': 86, '1999': 88, 'revival': 7465, '40s': 125, 'casablanca': 1462, 'cake': 1354, 'maggie': 5453, 'sara': 7707, 'freaks': 3703, 'controversial': 2058, 'workers': 9888, 'marred': 5540, 'loneliness': 5345, 'moronic': 5880, 'insisted': 4671, 'blatant': 1048, 'advertising': 299, 'franchise': 3688, 'pun': 7022, 'digest': 2617, 'bar': 837, 'ripoff': 7511, 'adolescent': 280, 'prejudice': 6841, 'heading': 4211, 'notions': 6152, 'respectable': 7412, 'salvage': 7685, 'marlene': 5536, 'grandparents': 3993, 'bye': 1342, 'awkwardly': 787, 'wounded': 9910, 'defense': 2429, 'kate': 4963, 'jerk': 4859, 'blank': 1045, 'relatives': 7303, 'knocked': 5047, 'jackass': 4816, 'nest': 6056, 'egg': 2965, 'buys': 1339, 'beer': 911, 'thumbs': 9041, 'noises': 6108, 'saturday': 7727, 'skull': 8176, 'val': 9466, 'kilmer': 5017, 'mcdermott': 5614, 'josh': 4908, 'addict': 255, 'aftermath': 323, 'mass': 5567, 'serving': 7927, 'capture': 1415, 'masterson': 5579, 'nathan': 6001, 'detroit': 2571, 'sarah': 7708, 'lena': 5201, 'triumphs': 9252, 'beg': 917, 'deluise': 2463, 'buildings': 1287, 'messy': 5700, 'martino': 5553, 'scorpion': 7784, 'tail': 8827, 'giallo': 3870, 'heyday': 4277, 'insurance': 4694, 'subsequently': 8649, 'clad': 1705, 'assassin': 671, 'brutality': 1262, 'bruno': 1259, 'crystal': 2259, 'maniac': 5499, 'dudley': 2858, 'liza': 5316, 'hokey': 4333, 'horrid': 4386, 'understated': 9351, 'pierce': 6637, 'brosnan': 1251, 'attenborough': 719, 'nations': 6004, 'adopted': 281, 'decades': 2398, 'combat': 1844, 'ali': 389, 'filthy': 3497, 'champion': 1542, 'fried': 3718, 'resort': 7409, 'tolerable': 9095, 'annoy': 513, 'behave': 925, 'conditions': 1960, 'warrior': 9670, 'blurry': 1086, 'informs': 4635, 'earn': 2908, 'disappearing': 2650, 'hiding': 4283, 'noise': 6107, 'bang': 832, 'surely': 8739, 'pitch': 6652, 'subtitles': 8655, 'fifteen': 3469, 'sat': 7715, 'continually': 2037, 'progressed': 6940, 'weeks': 9728, 'chu': 1675, 'yuen': 9977, 'secretary': 7838, 'witness': 9852, 'assigned': 677, 'miracles': 5768, 'sparse': 8350, 'skin': 8168, 'cities': 1698, 'cruel': 2248, 'isolation': 4798, 'affairs': 306, 'advanced': 291, 'firstly': 3528, '24': 109, '2002': 95, 'bittersweet': 1029, 'employs': 3036, 'cue': 2263, 'robby': 7542, 'accidental': 196, 'pakeezah': 6413, 'coverage': 2152, 'fluid': 3593, 'strain': 8563, 'depicts': 2509, 'tragedy': 9172, 'simultaneously': 8123, 'gathering': 3817, 'drum': 2845, 'bollywood': 1105, 'corners': 2104, 'whatsoever': 9759, 'repeats': 7367, 'remaining': 7328, 'copies': 2092, 'lays': 5160, 'capturing': 1418, 'forbidden': 3629, 'jordan': 4905, 'exposure': 3293, 'participation': 6463, 'rights': 7505, 'devastating': 2573, 'sections': 7842, 'finale': 3499, 'recognized': 7228, 'threaten': 9015, 'system': 8817, 'stevenson': 8522, 'measure': 5634, 'stranger': 8568, 'fleeing': 3561, 'profit': 6931, 'abilities': 155, 'porter': 6764, 'convinces': 2078, 'hire': 4310, 'yacht': 9944, 'cruise': 2251, 'anders': 475, 'seas': 7823, 'convicted': 2074, 'verdict': 9507, 'carnival': 1443, 'knocks': 5049, 'interests': 4722, 'blond': 1068, 'othello': 6325, 'devoid': 2585, 'planes': 6671, 'filler': 3485, 'lol': 5340, 'improved': 4553, 'unfortunate': 9373, 'nominations': 6113, 'papers': 6435, 'published': 7013, 'fencing': 3444, 'betrayal': 978, 'novelist': 6156, 'appreciation': 582, 'dante': 2340, 'collaboration': 1816, 'darkly': 2348, 'infected': 4619, 'unsatisfying': 9414, 'females': 3439, 'unwatchable': 9425, 'hug': 4417, 'guessing': 4065, 'dung': 2873, 'il': 4496, 'roller': 7570, 'hacks': 4099, 'mcadams': 5608, 'cillian': 1683, 'murphy': 5944, 'passable': 6475, '28': 114, 'kicked': 4999, 'hockey': 4331, 'terrorist': 8932, 'steal': 8495, 'gum': 4075, 'terrorists': 8933, 'oblivious': 6188, 'pedestrian': 6526, 'thompson': 9003, 'eh': 2969, 'wears': 9717, 'titled': 9078, 'se': 7814, 'expensive': 3256, 'stinker': 8536, 'victorian': 9532, 'titanic': 9076, 'harbor': 4151, 'strike': 8587, 'spring': 8419, 'eliminate': 2993, 'capitalism': 1404, 'communism': 1886, 'depict': 2504, 'contribution': 2052, 'quarter': 7061, 'similarly': 8113, 'mustache': 5956, 'bread': 1193, 'map': 5515, 'clay': 1730, 'berlin': 969, 'historically': 4318, 'phillip': 6602, 'civilians': 1703, 'revealing': 7452, 'relevant': 7314, 'stranded': 8565, 'intensely': 4707, 'slut': 8221, 'sneaking': 8250, 'psychologist': 7006, 'liz': 5315, 'examples': 3207, 'vertigo': 9517, 'bernard': 970, 'influence': 4625, 'partially': 6460, 'clunky': 1789, 'breasts': 1201, 'visceral': 9573, 'controls': 2057, 'conservative': 2000, 'shirts': 8028, 'staging': 8438, 'characteristic': 1563, 'angles': 492, 'tracking': 9163, 'distant': 2698, 'dropped': 2835, 'glove': 3919, 'integrated': 4697, 'occurs': 6215, 'underused': 9354, 'exit': 3244, 'necessary': 6025, 'comfortable': 1860, 'unfold': 9369, 'cheated': 1593, 'survived': 8760, 'remakes': 7331, 'da': 2301, 'liam': 5236, 'neeson': 6035, 'casper': 1467, 'friendly': 3720, 'cain': 1352, 'smoke': 8239, 'vanessa': 9478, 'kim': 5018, 'wendt': 9739, 'wig': 9802, 'varma': 9488, 'ki': 4997, 'sholay': 8039, 'pains': 6403, 'claims': 1709, 'borrow': 1139, 'climbs': 1757, 'ajay': 363, 'pistol': 6650, 'trigger': 9243, 'spared': 8347, 'agony': 339, 'partners': 6470, 'depends': 2503, 'hindi': 4301, 'raj': 7114, 'brooding': 1246, 'amitabh': 454, 'bachchan': 797, 'miserably': 5778, 'link': 5286, 'wrestler': 9919, 'wrestling': 9920, 'rampage': 7121, 'giggle': 3879, 'weapons': 9714, 'existent': 3241, 'violin': 9564, 'insulted': 4691, 'echo': 2929, 'fades': 3334, 'cinematographer': 1689, 'transform': 9186, 'drivel': 2828, 'elevator': 2990, 'casual': 1476, 'suits': 8698, 'culp': 2265, 'columbo': 1841, 'villains': 9555, 'cassidy': 1469, 'hires': 4312, 'report': 7375, 'deepest': 2422, 'maturity': 5596, 'richly': 7486, 'lightly': 5256, 'italy': 4806, 'leila': 5199, 'suffice': 8684, 'nineties': 6093, 'expressed': 3295, 'cynicism': 2298, 'grandfather': 3989, 'inform': 4630, '90s': 145, 'conceit': 1941, 'ala': 369, 'ho': 4329, 'palm': 6422, 'reactions': 7177, 'dense': 2489, 'maria': 5521, 'struggled': 8605, 'required': 7391, '1980': 67, 'misty': 5799, 'pamela': 6426, 'seymour': 7954, 'causing': 1493, 'complications': 1925, '1976': 63, 'settings': 7934, 'yearning': 9950, 'bats': 872, 'employed': 3032, 'unsettling': 9416, 'fifty': 3472, 'consists': 2011, 'bitten': 1027, 'vacation': 9461, 'ruined': 7626, 'reference': 7257, 'raving': 7162, 'sweat': 8785, 'cheaper': 1590, 'muppets': 5934, 'insist': 4670, 'forgets': 3641, 'eighty': 2972, 'sketches': 8163, 'dreadfully': 2808, 'amok': 455, 'bright': 1225, 'rookie': 7587, 'foxx': 3680, 'alvin': 431, 'morse': 5883, 'regime': 7277, '1989': 77, 'belushi': 952, 'rotten': 7604, 'tow': 9148, 'sporting': 8409, 'goods': 3951, 'hamilton': 4116, 'lengthy': 5205, 'criticized': 2227, 'elvira': 3005, 'rambling': 7117, 'acquaintance': 224, 'intricate': 4739, 'delighted': 2452, 'colin': 1815, 'holland': 4340, 'mothers': 5892, 'idle': 4483, 'damsel': 2319, 'distress': 2709, 'flavor': 3555, 'francis': 3689, 'nielsen': 6084, 'commander': 1866, 'adams': 247, 'distinguished': 2702, 'id': 4469, 'stevens': 8521, 'doc': 2728, 'electronic': 2984, 'krell': 5063, 'toes': 9088, 'scientific': 7774, 'enigmatic': 3077, 'morbius': 5870, 'prop': 6965, 'complexities': 1922, 'psychology': 7007, 'deliberately': 2447, 'confront': 1973, 'pushes': 7044, 'gates': 3814, 'operate': 6279, 'carefully': 1428, 'crafted': 2167, 'realization': 7196, 'multiple': 5928, 'flashbacks': 3549, 'leather': 5179, 'youth': 9973, 'wounds': 9911, 'recalls': 7215, 'vignettes': 9549, 'suave': 8638, 'mannerisms': 5508, 'shoulders': 8059, 'cameron': 1371, 'flea': 3560, 'barker': 843, 'wisely': 9839, 'ambiance': 442, 'reckless': 7224, 'completed': 1919, 'rolled': 7569, 'europeans': 3168, 'stills': 8532, 'varying': 9489, 'connery': 1987, 'dustin': 2881, 'hector': 4234, 'hunters': 4445, 'dragon': 2789, 'mythical': 5976, 'dreaming': 2810, 'asia': 657, 'eastern': 2919, 'promoting': 6959, 'worm': 9894, 'erika': 3132, 'comprehend': 1932, 'filling': 3486, 'severely': 7945, 'fluff': 3592, 'reasonable': 7205, 'ticket': 9045, 'uwe': 9460, 'boll': 1104, 'tempted': 8909, 'assure': 690, 'proof': 6964, 'filth': 3496, 'trend': 9228, 'influences': 4627, 'hostel': 4397, 'hyper': 4459, 'prisoners': 6903, 'mute': 5960, 'slaughtered': 8190, '666': 135, 'bag': 814, 'retarded': 7436, 'spree': 8418, 'fanatic': 3365, 'dumber': 2869, 'refuse': 7268, 'remark': 7332, 'smashes': 8232, 'masterfully': 5574, 'waking': 9624, 'germans': 3857, 'hustler': 4453, 'debra': 2394, 'winger': 9824, 'quaid': 7054, 'breaking': 1197, 'waves': 9698, 'reincarnation': 7288, 'tank': 8846, 'dan': 2320, 'occult': 6209, 'graphics': 3998, 'linear': 5281, 'criterion': 2221, 'radical': 7097, 'automatic': 759, 'pornographic': 6761, 'testimony': 8940, 'diary': 2596, 'pivotal': 6658, 'quirks': 7079, 'degrees': 2442, 'cleverly': 1739, 'bridget': 1221, 'exquisite': 3300, 'lords': 5363, 'snakes': 8246, 'meaningful': 5627, 'polish': 6735, 'prank': 6819, 'inducing': 4605, 'cringing': 2214, 'interactions': 4717, 'combined': 1847, 'forgivable': 3644, 'youtube': 9976, 'concentrates': 1944, 'fathers': 3399, 'tess': 8936, 'reese': 7253, 'witherspoon': 9849, 'sweden': 8786, 'degree': 2441, 'folk': 3608, 'musician': 5951, 'choir': 1643, 'austria': 749, 'echoes': 2930, 'revolt': 7466, 'hostile': 4398, 'corny': 2105, 'magazines': 5452, 'frail': 3682, 'radar': 7095, 'nevada': 6062, 'hardest': 4156, 'shelves': 8010, 'stores': 8555, 'slashers': 8187, 'rebels': 7213, 'princess': 6893, 'hunter': 4444, 'impress': 4544, 'animations': 501, 'chicks': 1624, 'tasty': 8866, 'ralph': 7115, 'bakshi': 819, 'backwards': 805, 'happenings': 4145, 'witnesses': 9854, 'ahem': 345, 'subdued': 8640, 'imprisoned': 4550, 'toole': 9119, 'honorable': 4363, 'telly': 8904, 'stooges': 8549, 'bothers': 1149, 'scooby': 7778, 'doo': 2757, 'chuckles': 1678, 'sesame': 7928, 'bear': 885, 'magician': 5457, 'bert': 973, 'ernie': 3134, 'passing': 6480, 'whip': 9776, 'frye': 3738, 'peterson': 6588, 'invites': 4763, 'susan': 8765, 'befriends': 916, 'suburban': 8660, 'corporations': 2108, 'climb': 1755, 'dig': 2616, 'dandy': 2328, 'stretched': 8582, 'relax': 7304, 'concentrate': 1943, 'meanings': 5629, 'choices': 1642, 'bless': 1057, 'similarity': 8112, 'inane': 4562, 'spare': 8346, 'standout': 8455, 'letdown': 5224, 'judged': 4919, 'generous': 3838, 'irwin': 4790, 'bloke': 1067, 'crocodile': 2230, 'ate': 700, 'poison': 6723, 'battling': 877, 'structured': 8603, 'fifth': 3470, 'bold': 1102, 'nazis': 6015, 'miniseries': 5757, 'delve': 2464, 'psyche': 7000, 'goebbels': 3931, 'destined': 2553, 'nuns': 6175, 'burton': 1316, 'plodding': 6701, 'genuinely': 3849, 'origin': 6309, 'disasters': 2658, 'allowing': 410, 'havoc': 4197, 'crushing': 2254, 'dynamite': 2896, 'intent': 4709, 'korean': 5060, 'mourning': 5905, 'dislike': 2685, 'indication': 4598, 'introducing': 4747, 'tested': 8939, 'randomly': 7128, 'rampant': 7122, 'slower': 8218, 'alot': 419, 'widowed': 9798, 'employee': 3033, 'pot': 6797, 'plant': 6676, 'enjoys': 3083, 'travelling': 9212, 'wore': 9884, 'sore': 8315, 'thumb': 9040, 'profoundly': 6934, 'insightful': 4666, 'traumatic': 9207, 'torturing': 9135, 'prolific': 6949, 'legacy': 5189, 'respects': 7417, 'commit': 1877, 'wound': 9909, 'cons': 1993, 'loaded': 5322, 'lay': 5156, 'stargate': 8465, 'sg': 7956, 'imagining': 4516, 'wolf': 9862, 'voters': 9607, 'predict': 6832, 'sleepwalkers': 8199, 'feed': 3424, 'proceeds': 6912, 'amidst': 452, 'showcase': 8065, 'muddled': 5926, 'puzzled': 7050, 'perry': 6566, 'randy': 7129, 'graceful': 3976, 'losing': 5372, 'carey': 1433, 'medicine': 5642, 'café': 1349, 'waitress': 9620, 'mildred': 5732, 'realizing': 7200, 'engagement': 3066, 'emil': 3017, 'flirting': 3577, 'nora': 6123, 'fay': 3411, 'shelter': 8009, 'frances': 3687, 'dee': 2416, 'mates': 5586, 'prepare': 6849, 'kitsch': 5035, 'ballet': 826, 'parent': 6445, 'sexuality': 7951, 'stirring': 8538, 'ignorant': 4488, 'mysticism': 5974, 'confuse': 1978, 'berkeley': 968, 'prophet': 6971, 'coach': 1792, 'elizabeth': 2996, 'ellen': 2998, 'homicidal': 4353, 'asylum': 698, 'anthology': 526, 'collins': 1829, 'macabre': 5434, 'keeper': 4975, 'segments': 7864, 'poker': 6726, 'crucial': 2246, 'coma': 1843, 'bondage': 1111, 'euro': 3164, 'apes': 556, 'bradford': 1176, 'teamed': 8880, 'complains': 1914, 'outlandish': 6342, 'banter': 836, 'intentional': 4711, 'hears': 4219, 'arrived': 634, 'shares': 7985, 'asset': 676, 'shocks': 8035, 'pizza': 6660, 'whipped': 9777, 'urban': 9441, 'memoirs': 5667, 'miscast': 5775, 'global': 3911, 'debate': 2391, 'einstein': 2973, 'testing': 8941, 'shore': 8047, 'lance': 5100, 'marvelously': 5558, 'winters': 9833, 'tide': 9047, 'dangerously': 2333, 'stern': 8518, 'overbearing': 6356, 'logan': 5336, 'mae': 5449, 'slew': 8204, 'crisp': 2217, 'wells': 9737, 'hitchhiker': 4322, 'galaxy': 3783, 'bliss': 1061, 'korda': 5058, 'cedric': 1500, 'richardson': 7485, 'massey': 5570, 'preachy': 6825, 'citizens': 1700, 'literal': 5304, 'explodes': 3275, 'gas': 3811, 'remembers': 7339, 'bullying': 1296, 'fuel': 3740, 'lands': 5105, 'screens': 7800, 'warns': 9667, 'criticize': 2226, 'foley': 3607, 'ideals': 4472, 'millennium': 5738, 'explicit': 3273, 'exploits': 3281, 'wonders': 9873, 'scarface': 7751, 'castro': 1474, 'cuban': 2261, 'thankful': 8950, 'records': 7236, 'rid': 7490, 'stepped': 8511, 'lopez': 5361, 'currently': 2279, 'manny': 5510, 'gain': 3779, 'cocaine': 1797, 'iron': 4779, 'engrossing': 3073, 'emotionally': 3024, 'pfeiffer': 6592, 'integral': 4696, 'stoic': 8540, 'murray': 5945, 'omar': 6261, 'peckinpah': 6524, 'depicting': 2506, 'periods': 6560, 'duties': 2883, 'peers': 6529, 'products': 6924, 'obsolete': 6200, 'appreciated': 581, 'colonel': 1831, 'pertwee': 6578, 'busey': 1321, 'gloomy': 3913, 'continuous': 2043, 'edgy': 2939, 'dragons': 2790, 'obligatory': 6186, 'lab': 5077, 'blob': 1063, 'cave': 1495, 'vital': 9588, 'meredith': 5687, 'barbra': 839, 'dismiss': 2688, 'descent': 2523, 'esther': 3155, 'outset': 6350, 'responds': 7419, 'inexplicably': 4616, 'shamelessly': 7977, 'kristofferson': 5067, 'managing': 5493, 'seller': 7872, 'bee': 909, 'kenny': 4987, 'evergreen': 3182, '2006': 99, 'peters': 6587, 'wardrobe': 9655, 'introduce': 4744, 'mysteries': 5969, 'abruptly': 168, 'cycle': 2296, 'mathieu': 5587, 'competitive': 1910, 'signal': 8096, 'loony': 5358, 'spin': 8381, 'rangers': 7131, 'rifle': 7500, 'encouraged': 3045, 'picking': 6629, 'recovering': 7238, 'unexpectedly': 9364, 'wwi': 9940, 'mobster': 5814, 'valentine': 9467, 'senses': 7887, 'rumors': 7634, 'dis': 2644, 'illegal': 4498, 'sanity': 7703, 'scoop': 7779, 'dominated': 2749, 'software': 8273, 'approved': 591, 'tastes': 8865, 'satisfaction': 7721, 'rewarding': 7474, 'creek': 2200, 'breeze': 1209, 'effortless': 2962, 'blunt': 1084, 'arquette': 627, 'inability': 4558, 'misguided': 5783, 'campus': 1377, 'target': 8854, 'mia': 5711, 'brow': 1255, 'smarter': 8230, 'tended': 8913, 'convention': 2063, 'lump': 5414, 'darling': 2350, 'clint': 1758, 'residents': 7403, 'disorder': 2690, 'indians': 4596, 'wilderness': 9805, 'brennan': 1212, 'border': 1131, 'dust': 2880, 'ruled': 7631, 'tightly': 9055, 'gannon': 3796, 'mcintire': 5617, 'relaxed': 7305, 'interaction': 4716, 'talky': 8843, 'lend': 5202, 'overblown': 6357, 'mice': 5713, 'mormon': 5876, 'mormons': 5877, 'richards': 7484, 'duff': 2861, 'ace': 214, 'emma': 3019, 'sneak': 8249, 'jesus': 4867, 'forgetting': 3643, 'wine': 9822, 'doubts': 2770, 'extra': 3305, 'appeals': 567, 'capacity': 1401, 'compassion': 1900, 'hello': 4245, 'buster': 1326, 'ramones': 7120, 'gather': 3815, 'surrogate': 8753, 'micheal': 5716, 'des': 2521, 'hoot': 4369, 'conveys': 2072, 'empathy': 3026, 'stronger': 8598, 'dozens': 2782, 'bumbling': 1298, 'posing': 6780, 'january': 4835, 'opinions': 6284, 'forum': 3668, 'viewpoint': 9545, 'retrospect': 7441, 'uncertain': 9328, 'pierre': 6638, 'transparent': 9197, 'antwerp': 537, 'analysis': 469, 'loach': 5320, 'cultures': 2269, 'establishment': 3153, 'glorious': 3915, 'ram': 7116, 'gopal': 3955, 'deol': 2496, 'scripting': 7808, 'pc': 6516, 'pakistan': 6414, 'paulie': 6504, 'enters': 3096, 'maurice': 5600, 'legitimate': 5195, 'anticipated': 530, 'span': 8344, 'parade': 6437, 'parodies': 6453, 'minimum': 5754, 'hart': 4175, 'redneck': 7248, 'bash': 856, 'akshay': 367, 'kumar': 5071, 'kareena': 4958, 'album': 377, 'dialogs': 2590, 'cheech': 1598, 'chong': 1646, 'sleaze': 8194, 'werewolf': 9745, 'wang': 9644, 'camps': 1376, 'veterans': 9521, '16': 13, 'betty': 985, 'duh': 2863, 'hyped': 4458, 'joint': 4895, 'btw': 1267, 'portrayals': 6771, 'mentality': 5676, 'yugoslavia': 9978, 'meteor': 5704, 'crashes': 2173, 'crater': 2176, 'update': 9431, 'mister': 5797, 'ants': 536, 'wrought': 9933, '1963': 49, 'martian': 5550, 'readers': 7180, 'romero': 7582, 'dawn': 2368, 'shirley': 8026, 'magically': 5456, 'pattern': 6499, 'dumbest': 2870, 'alongside': 418, 'conveying': 2071, 'pale': 6418, 'freaked': 3701, 'hometown': 4352, 'graveyard': 4006, 'dug': 2862, 'satan': 7716, 'recommendation': 7230, 'engine': 3068, 'benny': 961, 'proceed': 6910, 'banal': 829, 'philadelphia': 6600, 'investigator': 4758, 'inadvertently': 4561, 'snuff': 8259, 'ghetto': 3866, 'mac': 5433, 'capital': 1403, 'astounding': 696, 'styled': 8634, 'ma': 5431, 'colony': 1833, 'vapid': 9482, 'remarkably': 7334, 'campbell': 1374, 'globe': 3912, 'developments': 2578, 'freaky': 3704, 'crop': 2233, 'proportions': 6973, 'involve': 4764, 'sheen': 8000, 'rex': 7475, 'mccarthy': 5611, 'directs': 2641, 'boasts': 1090, 'distraction': 2707, 'accents': 186, 'boyer': 1167, 'greek': 4018, 'lorre': 5366, 'policy': 6734, 'greta': 4026, 'garbo': 3801, 'swedish': 8787, 'exclusive': 3225, 'gathered': 3816, 'data': 2356, 'biography': 1014, 'ranch': 7124, 'spirits': 8388, 'assorted': 685, 'girlfriends': 3891, 'rude': 7623, 'abusive': 182, 'messing': 5699, 'drastically': 2799, 'thirds': 8996, 'jill': 4876, 'tame': 8845, 'stiller': 8531, 'aniston': 505, 'limp': 5276, '3000': 118, 'suspension': 8773, 'wagner': 9616, 'mechanical': 5638, 'rumor': 7633, 'volume': 9599, 'demented': 2469, 'status': 8489, 'taboo': 8821, 'pursuit': 7041, 'rightly': 7504, 'translated': 9195, 'characteristics': 1564, 'shopping': 8045, 'jungle': 4937, 'jess': 4863, 'diabolical': 2588, 'cliff': 1748, 'suburbia': 8661, 'civilization': 1704, 'item': 4807, 'deer': 2424, 'geoffrey': 3850, 'murderers': 5938, 'butch': 1329, 'bite': 1023, 'howling': 4413, 'favour': 3406, 'assist': 679, 'appropriately': 589, 'crashed': 2172, 'ruining': 7627, 'soooo': 8307, 'stab': 8428, 'boob': 1117, 'popping': 6753, 'immature': 4521, 'mendes': 5674, 'origins': 6314, 'eldest': 2979, 'weaker': 9707, 'praise': 6816, 'anytime': 547, 'perlman': 6563, 'abortion': 161, 'badness': 812, 'inferior': 4621, 'criteria': 2220, 'thread': 9013, 'fingers': 3509, 'shaped': 7982, 'frames': 3685, 'diane': 2595, 'unlikeable': 9401, 'mouthed': 5908, 'repressed': 7385, 'prostitute': 6976, 'characterizations': 1566, 'turturro': 9288, 'chess': 1614, 'watson': 9695, 'consciousness': 1996, 'quasi': 7063, 'rings': 7508, 'misleading': 5784, 'lurid': 5421, 'distributors': 2712, 'mill': 5737, 'shocker': 8032, 'slash': 8185, 'pleasantly': 6693, 'somber': 8287, 'paxton': 6507, 'booth': 1128, 'simpler': 8117, 'scale': 7741, 'eats': 2925, 'monks': 5845, 'resulting': 7431, 'resembling': 7400, 'eagerly': 2900, 'vampires': 9475, 'speechless': 8364, 'pal': 6415, 'contemplating': 2027, 'heres': 4263, 'genetic': 3839, 'boogeyman': 1119, 'forgiven': 3646, 'september': 7904, 'policemen': 6732, 'ing': 4636, 'matches': 5583, 'platform': 6680, 'enormous': 3085, 'fixed': 3540, 'justified': 4945, '33': 120, 'deemed': 2419, 'scan': 7743, 'heartwarming': 4225, 'panic': 6430, 'kazan': 4970, 'april': 593, 'laboratory': 5081, 'efficient': 2960, 'atomic': 705, 'industrial': 4609, 'discussed': 2671, 'clark': 1715, 'management': 5490, 'arriving': 636, 'principles': 6897, 'st': 8427, 'warfare': 9657, 'presume': 6868, 'commando': 1868, 'espionage': 3145, '1942': 33, '23': 108, '200': 92, 'covering': 2154, 'applause': 575, 'abbott': 152, 'costello': 2120, 'swords': 8802, 'repetitive': 7368, 'unconscious': 9332, 'studied': 8614, 'zizek': 9989, 'freud': 3716, 'noel': 6105, 'physics': 6623, 'professor': 6929, 'stephanie': 8508, 'stella': 8505, 'perverted': 6583, 'hybrid': 4455, 'adventurous': 296, 'shotgun': 8055, 'teachers': 8876, 'odyssey': 6223, 'manga': 5497, 'fought': 3672, 'majestic': 5469, 'austen': 745, 'artificial': 644, 'sufficient': 8685, 'samantha': 7688, 'psychic': 7003, 'drugged': 2843, 'mandatory': 5495, 'commits': 1879, 'denouement': 2488, 'daisies': 2308, 'whimsical': 9773, 'eddie': 2934, 'sammi': 7690, 'recording': 7235, 'siblings': 8080, 'neighbors': 6041, 'harmless': 4166, 'poke': 6724, 'worship': 9901, 'tomb': 9102, '19th': 89, 'kingdom': 5025, 'yarn': 9946, 'palace': 6416, 'egypt': 2967, 'sophisticated': 8310, 'egyptian': 2968, 'taxi': 8870, '1981': 69, 'agenda': 332, 'accurately': 211, 'chuckle': 1677, 'rebecca': 7209, 'flame': 3544, 'christie': 1668, 'bates': 866, 'frankie': 3694, 'dirty': 2643, 'complement': 1917, 'italians': 4805, 'danced': 2323, 'invested': 4754, 'ritter': 7523, 'rational': 7157, '4th': 127, '3rd': 123, 'shortened': 8050, 'surgery': 8744, 'amy': 466, 'extensive': 3302, 'paramount': 6442, 'vaudeville': 9492, 'organ': 6303, 'accompany': 201, 'en': 3038, 'gestures': 3861, 'showcases': 8066, 'ricardo': 7480, 'cortez': 2118, 'foolish': 3621, 'adequately': 266, 'divine': 2721, 'goings': 3935, 'barry': 848, 'nash': 5997, 'lt': 5399, 'spotlight': 8412, 'detectives': 2566, 'deputy': 2515, 'file': 3481, 'motions': 5895, 'array': 629, 'strongest': 8599, 'criminally': 2210, 'forbes': 3628, 'sly': 8223, 'oz': 6384, 'advances': 292, 'useful': 9449, 'disappears': 2651, 'juice': 4925, 'colleagues': 1821, 'cream': 2182, 'upbeat': 9429, 'bombs': 1108, 'shaking': 7970, 'permanently': 6565, 'users': 9452, 'karen': 4959, 'godzilla': 3930, 'revolving': 7471, '1974': 61, 'praising': 6818, 'romp': 7583, 'packs': 6393, 'expects': 3253, 'battlefield': 874, 'blurred': 1085, 'fourth': 3677, 'someday': 8290, 'dash': 2354, 'factory': 3329, 'lecture': 5183, 'landscapes': 5107, 'paints': 6409, 'tips': 9071, 'dreck': 2814, 'plagued': 6667, 'skeptical': 8161, 'gadgets': 3776, 'holly': 4342, 'norris': 6129, 'cocky': 1800, 'terrorism': 8931, 'downtown': 2780, 'pee': 6528, 'shops': 8046, 'cents': 1522, 'spiral': 8385, 'arranged': 628, 'couples': 2141, 'blending': 1055, 'bus': 1318, 'hadley': 4101, 'marylee': 5561, 'oil': 6247, 'slim': 8211, 'drinking': 2825, 'conniving': 1988, 'smitten': 8238, 'restrained': 7427, 'seeming': 7857, 'suspicion': 8774, 'chef': 1607, 'originals': 6313, 'mario': 5526, 'usa': 9445, 'hating': 4188, 'anniversary': 511, 'worlds': 9892, 'mexico': 5708, 'monday': 5838, 'occupied': 6211, 'earl': 2904, 'predator': 6829, 'novelty': 6158, 'scifi': 7777, 'vcr': 9494, 'fascination': 3384, 'objects': 6185, 'textbook': 8944, 'lawn': 5152, 'wheeler': 9762, 'abroad': 166, 'promised': 6954, 'refused': 7269, 'replacing': 7371, 'duck': 2855, 'additionally': 261, 'sang': 7702, 'peaceful': 6518, 'distributed': 2710, 'sober': 8263, 'snowman': 8257, 'lil': 5268, 'underwear': 9356, 'kidnapping': 5008, 'improbable': 4551, 'crawford': 2178, 'bronson': 1244, 'muscle': 5946, 'answering': 523, 'runaway': 7636, 'fashioned': 3388, 'generated': 3834, 'khan': 4995, 'approached': 585, 'earning': 2911, 'publicity': 7012, 'premiere': 6844, 'expose': 3290, 'schools': 7770, 'crosses': 2237, '1931': 21, 'transport': 9199, 'personnel': 6573, 'curiously': 2276, 'brent': 1213, 'economic': 2931, 'jewels': 4872, 'jealousy': 4848, 'employees': 3034, 'confronting': 1976, 'lesbians': 5216, 'theories': 8973, 'educated': 2948, 'wray': 9916, 'warehouse': 9656, 'guarantee': 4057, 'observations': 6194, 'pole': 6729, 'kidnap': 5006, 'swimming': 8792, 'fling': 3574, 'coward': 2157, 'clarence': 1713, 'creep': 2201, 'jeremy': 4858, 'hound': 4402, '2008': 101, 'eighties': 2971, 'blockbusters': 1066, 'harlin': 4163, 'cliffhanger': 1749, 'viggo': 9547, 'mortensen': 5885, 'excess': 3218, 'highlights': 4289, 'annoys': 518, 'mutants': 5958, 'dares': 2343, 'iranian': 4773, 'iran': 4772, 'towers': 9152, 'flashes': 3550, 'jumping': 4934, 'israel': 4799, 'shouting': 8062, 'hitting': 4325, 'retirement': 7438, 'coburn': 1796, 'robbery': 7538, 'deserts': 2531, 'garfield': 3806, 'showdown': 8067, '1966': 52, 'distracted': 2705, 'bosses': 1142, 'carnage': 1442, 'shield': 8016, 'griffith': 4031, 'boobs': 1118, 'leon': 5211, 'romances': 7576, 'gilbert': 3881, 'counter': 2129, 'refer': 7256, 'dancer': 2324, 'recommending': 7232, 'defeat': 2425, 'bing': 1012, 'crosby': 2234, 'burst': 1312, 'decorated': 2414, 'slips': 8214, 'canon': 1395, 'mann': 5505, 'format': 3652, 'roberts': 7544, 'reserved': 7401, 'geeks': 3823, 'imply': 4538, 'rounded': 7608, 'indulgent': 4608, 'envy': 3117, 'spoofs': 8405, 'translate': 9194, 'fuller': 3746, 'jacknife': 4820, 'driver': 2830, 'precisely': 6828, 'moreover': 5873, 'hayward': 4203, 'subtleties': 8657, 'slugs': 8220, 'mutated': 5959, 'toxic': 9157, 'promptly': 6961, 'juan': 4915, 'kari': 4960, 'profile': 6930, 'glen': 3906, 'heather': 4228, 'stoltz': 8543, 'spread': 8417, 'adored': 284, 'lieutenant': 5244, 'faux': 3402, 'trusted': 9266, 'compliment': 1926, 'challenges': 1538, 'disappeared': 2649, 'lone': 5344, 'buffy': 1282, 'basinger': 861, 'babe': 790, 'carnosaur': 1444, 'grendel': 4025, 'beowulf': 965, 'hulk': 4424, 'stinks': 8537, 'bubble': 1269, 'foul': 3673, 'extraordinarily': 3306, 'alternately': 426, 'bursting': 1313, 'disgusted': 2681, 'additional': 260, 'scum': 7813, 'disgust': 2680, 'require': 7390, 'leaps': 5172, 'mortal': 5884, 'meg': 5651, 'potentially': 6800, 'playwright': 6691, 'jolly': 4901, 'auto': 757, 'natalie': 6000, 'grady': 3981, 'greengrass': 4022, 'bourne': 1157, 'stiles': 8529, 'strathairn': 8570, 'organization': 6305, 'courageous': 2143, 'hispanic': 4315, 'worthless': 9904, 'endure': 3056, 'wishing': 9843, 'dopey': 2763, 'species': 8356, 'stomach': 8544, 'motorcycle': 5901, 'informed': 4633, 'crawling': 2179, 'photograph': 6612, 'impressively': 4549, 'weather': 9719, 'yeti': 9960, 'leap': 5171, 'searched': 7821, 'evolved': 3197, 'meyers': 5709, 'fur': 3759, 'rates': 7152, 'fiend': 3466, 'ferry': 3446, 'fog': 3604, 'poem': 6712, 'crossing': 2238, 'manipulate': 5501, 'siege': 8091, 'announced': 512, 'http': 4414, 'www': 9942, '2009': 102, 'sammy': 7692, 'seats': 7828, 'stumbled': 8623, 'biker': 1002, 'boogie': 1120, 'bastard': 864, 'inheritance': 4643, 'incest': 4565, 'hatred': 4189, 'catchy': 1482, 'finney': 3514, 'capote': 1406, 'edwards': 2952, 'profession': 6926, 'olivier': 6257, 'spain': 8343, 'fascism': 3385, 'sue': 8679, 'applaud': 574, 'silliness': 8105, 'lighthearted': 5254, 'warmth': 9661, 'sol': 8274, '21st': 106, 'favours': 3409, 'copied': 2091, 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1046, 'mount': 5902, 'rivals': 7527, 'dresses': 2817, 'complained': 1912, 'phrases': 6619, 'coolest': 2086, 'anchor': 471, 'werewolves': 9746, 'blaxploitation': 1050, 'misunderstandings': 5800, 'distorted': 2703, 'spaces': 8340, 'diverse': 2719, 'knightley': 5043, 'beckham': 902, 'incidental': 4569, 'evolution': 3195, 'kathryn': 4965, 'afghanistan': 315, 'surgeon': 8743, 'casually': 1477, 'sniper': 8251, 'navy': 6013, 'proudly': 6987, 'emmanuelle': 3020, 'wong': 9875, 'transformation': 9187, 'politician': 6739, 'programme': 6936, 'dame': 2314, 'strikingly': 8590, 'confident': 1966, 'disappearance': 2648, 'obsessive': 6199, 'vulnerable': 9614, 'route': 7612, '1990s': 79, 'zack': 9980, 'marine': 5524, 'quinn': 7077, 'attended': 722, 'jacques': 4822, 'carla': 1438, 'request': 7389, 'fulfilling': 3744, 'remainder': 7326, 'uniformly': 9380, 'enhances': 3076, 'kerry': 4991, 'labour': 5082, 'spielberg': 8378, 'serials': 7914, 'battles': 875, 'lung': 5418, 'muni': 5932, 'farmer': 3377, 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'shoved': 8063, 'sprinkled': 8421, 'aiming': 354, 'suspicious': 8776, 'smallville': 8227, 'lionel': 5290, 'bart': 851, 'blends': 1056, 'saves': 7732, 'stealth': 8498, '2nd': 115, 'fulfilled': 3743, 'christy': 1673, 'achievements': 218, 'communicate': 1884, 'therapist': 8975, 'fiona': 3516, 'elmer': 3002, 'piper': 6647, 'disgrace': 2677, 'induced': 4604, 'rohmer': 7565, 'fix': 3539, 'culkin': 2264, 'outfit': 6339, '1965': 51, 'canceled': 1382, 'disliked': 2686, 'fleming': 3564, 'henchmen': 4255, 'habit': 4094, 'brides': 1218, 'wholesome': 9783, 'lane': 5108, 'ingenious': 4637, 'chat': 1585, 'bites': 1024, 'connect': 1982, 'hayden': 4201, 'portman': 6767, 'heights': 4237, 'christina': 1669, 'wheelchair': 9761, 'apple': 576, 'artwork': 651, 'skirt': 8173, 'chen': 1610, 'pang': 6429, 'ruthless': 7652, 'ensure': 3091, 'activity': 235, 'reminding': 7343, 'knives': 5045, 'mundane': 5931, 'armstrong': 621, 'capitalize': 1405, 'bowl': 1160, 'byron': 1344, 'inherited': 4644, 'morals': 5867, 'lovingly': 5391, 'recreation': 7239, 'virtual': 9568, 'empire': 3030, 'followers': 3612, 'beatty': 895, 'drivers': 2831, 'backed': 801, 'alcohol': 379, 'sounding': 8327, 'carmen': 1441, 'chopping': 1652, 'cheat': 1592, 'ambition': 445, 'burn': 1307, 'enduring': 3058, 'defeated': 2426, 'fools': 3622, 'shameless': 7976, 'senator': 7879, 'communist': 1887, 'ronald': 7585, 'reagan': 7185, 'pronounced': 6963, 'baked': 817, 'affected': 308, 'placing': 6665, 'helpless': 4251, 'hunted': 4443, 'baddie': 809, 'mentally': 5677, 'unstable': 9417, 'grip': 4035, 'exorcist': 3245, 'arguing': 607, 'vamp': 9473, 'brat': 1187, 'torch': 9127, 'examine': 3205, 'nation': 6002, 'fiasco': 3459, 'capra': 1407, 'vein': 9501, 'purposes': 7037, 'purchase': 7031, 'prints': 6899, 'dire': 2631, 'scriptwriters': 7811, 'betrayed': 979, 'republic': 7386, 'prevents': 6877, 'dressler': 2819, 'roscoe': 7598, 'opposition': 6291, 'myrtle': 5967, 'errol': 3137, 'flynn': 3597, 'height': 4236, 'gable': 3772, 'harlow': 4164, 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6196, 'mcqueen': 5620, 'theodore': 8972, 'randall': 7125, 'bounty': 1156, 'kissing': 5033, 'timer': 9062, 'absorbed': 173, 'sgt': 7957, 'supermarket': 8723, 'lunch': 5416, 'freeze': 3710, 'polar': 6728, 'ghostly': 3868, 'beverly': 987, 'liu': 5309, 'enchanted': 3039, 'spoiled': 8397, 'der': 2516, 'gretchen': 4027, 'mol': 5828, 'bettie': 984, 'profits': 6932, 'haines': 4104, 'peggy': 6531, 'boone': 1125, 'unbelievably': 9326, 'tobe': 9083, 'hooper': 4368, 'spontaneous': 8403, 'derek': 2518, 'tarzan': 8858, 'kolchak': 5056, 'malevolent': 5481, 'harrowing': 4172, 'feinstone': 3432, 'patients': 6495, 'chemical': 1608, 'adaptations': 250, '1993': 82, 'silverstone': 8108, 'sacrificed': 7659, 'fairytale': 3347, 'cousin': 2149, 'plotting': 6706, 'stifler': 8528, 'paycheck': 6509, 'brien': 1224, 'traveling': 9211, 'wtc': 9934, 'floors': 3582, 'firefighters': 3520, 'witnessing': 9855, 'races': 7088, 'gladly': 3899, 'steer': 8504, 'abomination': 160, 'vastly': 9491, 'wanders': 9643, 'kindly': 5021, 'chained': 1532, 'joining': 4893, 'suited': 8697, 'sack': 7657, 'bathtub': 870, 'liking': 5267, 'qualify': 7057, 'scarier': 7752, 'martians': 5551, 'exploring': 3286, 'fulci': 3741, 'zombi': 9992, 'rips': 7515, 'mattei': 5590, 'sane': 7701, 'companies': 1890, 'screened': 7796, '1939': 29, 'backwoods': 806, 'dreaded': 2806, 'lange': 5110, 'braveheart': 1189, 'benjamin': 960, '18th': 16, 'locals': 5327, 'traditions': 9170, 'sigh': 8092, '1964': 50, '1975': 62, 'marathon': 5516, 'fanatics': 3366, 'inconsistencies': 4582, 'lowe': 5393, 'shrill': 8076, 'initially': 4646, 'voted': 9606, 'peruvian': 6579, 'careful': 1427, 'worrying': 9899, 'alarm': 372, 'decency': 2402, 'collar': 1819, 'aditya': 267, 'saif': 7672, 'anil': 496, 'commendable': 1869, 'cells': 1511, 'passengers': 6478, 'seducing': 7846, 'salem': 7678, 'exceedingly': 3208, 'corey': 2098, 'wings': 9825, 'natali': 5999, 'cypher': 2299, 'vincenzo': 9558, 'wrap': 9913, 'stairs': 8439, 'definition': 2437, 'rack': 7094, 'sale': 7677, 'neill': 6044, 'rukh': 7629, 'benet': 959, 'radiation': 7096, 'melt': 5662, 'overboard': 6358, 'punk': 7027, 'shin': 8019, 'employ': 3031, 'lurking': 5422, 'agents': 334, 'ninja': 6095, 'pose': 6776, 'supply': 8726, 'marquis': 5539, 'villa': 9551, 'redeem': 7244, 'sheridan': 8013, 'operatic': 6280, 'parsifal': 6456, 'stripped': 8594, 'choosing': 1649, 'wondrous': 9874, 'rear': 7203, 'emerge': 3015, 'weary': 9718, 'stroke': 8596, 'conception': 1947, 'breakthrough': 1199, 'paragraph': 6439, 'crack': 2162, 'orphanage': 6318, 'sales': 7679, 'hawn': 4200, 'sink': 8138, 'handicapped': 4125, 'protective': 6983, 'burial': 1304, 'reiser': 7289, 'determine': 2568, 'liberties': 5239, 'thrilling': 9025, 'safely': 7668, '1998': 87, 'sr': 8426, 'bagdad': 815, 'sabu': 7656, 'conrad': 1991, 'veidt': 9500, 'jaffar': 4824, 'technicolor': 8887, 'stairway': 8440, 'demographic': 2472, 'bruckheimer': 1258, 'miranda': 5771, 'mankind': 5504, 'maverick': 5601, 'replies': 7373, 'systems': 8818, 'cecil': 1499, 'demille': 2470, 'picnic': 6631, 'fishing': 3532, 'singles': 8135, 'sox': 8337, 'reply': 7374, 'wizard': 9859, 'swordplay': 8801, 'clyde': 1790, 'parties': 6466, 'muslim': 5953, 'rejects': 7292, 'mobile': 5813, 'turkish': 9280, 'danish': 2338, 'expressing': 3297, '70s': 138, 'anxious': 540, 'overshadowed': 6367, 'motivated': 5896, 'wet': 9753, 'tendency': 8914, 'otto': 6329, 'preminger': 6846, 'grossly': 4041, 'suitably': 8695, 'scalise': 7742, 'cracking': 2164, 'enforcer': 3063, 'philo': 6604, 'twitch': 9300, 'paths': 6492, 'seagal': 7816, 'contend': 2030, 'hangs': 4135, 'moe': 5827, 'niece': 6083, 'curly': 2277, 'geeky': 3824, 'sarandon': 7709, 'ostensibly': 6324, 'fearless': 3414, 'vigilante': 9548, 'incidentally': 4570, 'raging': 7101, 'venezuela': 9502, 'economy': 2932, 'cheer': 1600, 'blast': 1047, 'lanza': 5114, 'pavarotti': 6506, 'breathe': 1203, 'irrational': 4783, 'corrupted': 2116, 'inspector': 4674, 'boyle': 1171, 'leaders': 5165, 'gods': 3929, 'solidly': 8281, 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9536, 'chamber': 1540, 'townspeople': 9156, 'crazed': 2180, 'links': 5288, 'unaware': 9323, 'committing': 1882, 'approaching': 587, 'thailand': 8947, 'tits': 9080, 'goat': 3926, 'chevy': 1617, 'shahid': 7965, 'amrita': 461, 'thieves': 8987, 'montrose': 5856, 'despicable': 2549, 'cunningham': 2271, 'mercilessly': 5684, 'torment': 9128, 'julian': 4928, 'unheard': 9377, 'gesture': 3860, 'stark': 8467, 'voiced': 9595, 'familiarity': 3360, 'inhabit': 4640, 'serbian': 7909, 'sid': 8084, 'attachment': 710, 'rabid': 7086, 'farm': 3376, 'attends': 724, 'intellectually': 4700, 'stimulating': 8534, 'vaguely': 9464, '1932': 22, 'swim': 8791, 'maureen': 5599, 'harilal': 4161, 'khanna': 4996, 'epitome': 3123, 'kamal': 4953, 'savalas': 7729, 'bloated': 1062, 'survival': 8758, 'youths': 9975, 'recognition': 7225, 'lukas': 5411, 'tourist': 9146, 'alligator': 407, 'inter': 4714, 'sofia': 8271, 'diaz': 2597, 'mccabe': 5610, 'shaky': 7971, 'mega': 5652, 'hardcore': 4153, 'noam': 6101, 'chomsky': 1645, 'chew': 1618, 'wherever': 9768, 'signature': 8097, 'slack': 8179, 'fighters': 3475, 'alley': 405, 'melbourne': 5656, 'posey': 6778, 'goldblum': 3938, 'enchanting': 3040, 'sweeping': 8788, '500': 129, 'ambiguity': 443, 'slavery': 8192, 'depictions': 2508, 'jake': 4827, 'herbert': 4260, 'chooses': 1648, 'heels': 4235, 'arty': 652, 'informer': 4634, 'morally': 5866, 'uneducated': 9360, 'dogma': 2738, 'carlisle': 1439, 'tho': 9001, 'lastly': 5127, 'screamed': 7792, 'languages': 5112, 'cancelled': 1383, 'listener': 5300, 'permanent': 6564, 'toni': 9111, 'collette': 1828, 'bald': 823, 'audrey': 740, 'marked': 5531, 'inexperienced': 4614, 'boyfriends': 1169, 'respectful': 7414, 'collapse': 1817, 'separately': 7903, 'achievement': 217, 'airing': 360, 'heroism': 4270, 'finnish': 3515, 'humane': 4427, 'confrontation': 1974, 'yell': 9952, 'supportive': 8731, 'gamut': 3789, 'evoke': 3193, 'domestic': 2747, 'unrelated': 9413, 'climbing': 1756, 'sorrow': 8317, 'forrest': 3659, 'hippies': 4309, 'penis': 6534, 'farewell': 3375, 'literature': 5307, 'slept': 8202, 'cards': 1422, 'mole': 5830, 'chapter': 1559, 'hi': 4278, 'protecting': 6981, 'poster': 6794, 'bills': 1009, 'waterfront': 9693, 'dani': 2335, 'hunger': 4439, 'endeavor': 3049, 'cliched': 1741, 'baddies': 810, 'frequent': 3713, '26': 112, 'hk': 4326, 'monumental': 5858, 'waited': 9618, 'incompetence': 4579, 'saints': 7675, 'minus': 5763, 'astonishingly': 695, 'displaying': 2693, 'famed': 3358, 'brooke': 1247, 'dental': 2490, 'smoothly': 8242, 'wakes': 9623, 'um': 9316, 'senior': 7883, 'devious': 2584, 'fuzzy': 3769, 'progressive': 6943, 'confined': 1967, 'breakfast': 1196, 'rave': 7161, 'kinski': 5029, 'kaufman': 4968, 'chainsaw': 1533, 'allegedly': 401, 'previews': 6879, 'theo': 8971, 'robertson': 7545, 'rejection': 7291, '21': 105, 'muppet': 5933, 'petiot': 6589, 'cloak': 1762, 'crooked': 2231, 'concentration': 1945, 'wartime': 9673, 'resurrection': 7435, 'jew': 4869, 'contestants': 2034, 'colman': 1830, 'firmly': 3525, 'jose': 4906, 'babes': 791, 'miike': 5728, 'gundam': 4078, 'pocket': 6710, 'net': 6057, 'devils': 2583, 'clooney': 1766, 'adaption': 252, 'antwone': 538, 'therapy': 8976, 'hmmm': 4328, 'marines': 5525, 'dinosaur': 2629, 'locke': 5333, 'showtime': 8073, 'fable': 3317, 'patch': 6488, 'inhabitants': 4641, 'marty': 5554, 'opponent': 6285, 'attacking': 713, 'ceiling': 1501, 'pleasing': 6696, 'partial': 6459, 'missions': 5793, 'timon': 9065, 'pumbaa': 7021, 'simba': 8109, 'perspectives': 6576, 'woke': 9861, 'lola': 5341, 'deliciously': 2450, 'items': 4808, 'elliott': 3000, 'wax': 9700, 'wolves': 9863, 'surround': 8754, 'firm': 3524, 'shockingly': 8034, 'separated': 7902, 'cartoonish': 1459, 'surfers': 8741, 'hum': 4425, 'assignment': 678, 'fassbinder': 3390, 'accounts': 208, 'observe': 6195, 'socially': 8266, 'lang': 5109, 'mistress': 5798, 'dose': 2766, 'pad': 6394, 'youngest': 9968, 'yells': 9955, 'lent': 5209, 'sights': 8094, 'collector': 1826, 'scandal': 7744, 'monologues': 5847, 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5632, 'suite': 8696, 'coincidences': 1810, 'ocean': 6216, 'jeep': 4852, 'masked': 5563, 'affleck': 313, 'throwaway': 9032, 'oshii': 6322, 'gardner': 3805, 'vera': 9505, 'graves': 4005, 'marvin': 5559, 'engineer': 3069, 'tickets': 9046, 'increasing': 4586, 'extremes': 3311, 'greg': 4023, 'preferably': 6838, 'noon': 6120, '01': 2, 'vice': 9526, 'versa': 9512, 'convent': 2062, 'bra': 1174, 'segal': 7862, 'insomnia': 4673, 'pixar': 6659, 'angst': 494, 'smuggling': 8244, 'stating': 8485, 'erik': 3131, 'marcel': 5518, 'phyllis': 6620, 'kent': 4988, 'coke': 1811, 'condemned': 1958, 'believer': 941, 'policies': 6733, 'samuel': 7693, 'virginia': 9566, 'chock': 1640, 'denis': 2484, 'exhilarating': 3237, 'implication': 4535, 'costner': 2121, 'keitel': 4979, 'timed': 9060, 'mcgavin': 5616, 'deeds': 2418, 'sopranos': 8313, 'cared': 1424, 'unnerving': 9406, 'mack': 5439, 'arise': 611, 'custody': 2287, 'puzzle': 7049, 'luc': 5401, 'dominic': 2750, 'connor': 1990, 'tucker': 9274, 'starship': 8471, '150': 12, 'fleet': 3562, 'counterpart': 2130, 'seberg': 7831, 'widower': 9799, 'nutty': 6180, 'jo': 4879, 'daphne': 2341, 'bullet': 1292, 'insists': 4672, 'sleeve': 8201, 'gunbuster': 4077, 'noriko': 6124, 'assembled': 675, 'confirmed': 1969, 'gripe': 4036, 'heroin': 4268, 'degrading': 2440, 'defies': 2430, 'pickford': 6628, 'mindset': 5748, 'capshaw': 1409, 'seattle': 7829, 'tokyo': 9093, 'psychopath': 7008, 'strained': 8564, 'lotr': 5376, 'deus': 2572, 'owe': 6374, 'illiterate': 4499, 'stretching': 8583, 'noticeable': 6147, 'sensation': 7884, 'applied': 577, 'midget': 5722, 'defy': 2439, 'ultimatum': 9314, 'stardust': 8462, 'han': 4121, 'construct': 2016, 'leia': 5197, 'ewoks': 3198, 'darth': 2353, 'skywalker': 8178, 'candle': 1387, 'anakin': 468, 'vehicles': 9499, 'wider': 9794, 'streep': 8574, 'flavia': 3554, 'medieval': 5643, 'jigsaw': 4875, 'contrasted': 2048, 'cher': 1611, 'lars': 5121, 'trier': 9241, 'anchors': 472, 'aweigh': 780, 'forties': 3663, 'benefits': 958, 'iturbi': 4811, 'athletic': 701, 'reasoning': 7207, 'bias': 991, 'goodman': 3949, 'auteur': 750, 'guinea': 4072, 'void': 9597, 'impersonation': 4533, 'overacting': 6354, 'nun': 6174, 'tool': 9117, 'pym': 7052, 'dorm': 2764, 'abound': 162, 'alter': 423, 'consist': 2008, 'transforms': 9191, 'yokai': 9963, 'disguised': 2679, 'drifter': 2823, 'madison': 5444, 'grinch': 4034, 'dodgy': 2734, 'gilliam': 3882, 'protection': 6982, 'shaolin': 7980, 'shearer': 7997, 'casino': 1466, 'takashi': 8828, 'prostitutes': 6977, 'orphan': 6317, 'blondell': 1070, 'reverend': 7456, 'thaw': 8956, 'christine': 1670, 'tomatoes': 9101, 'presidential': 6862, 'marketing': 5533, 'diver': 2718, 'tomato': 9100, 'correctness': 2113, 'rusty': 7650, 'modest': 5824, 'hooker': 4367, 'contestant': 2033, 'accomplish': 203, 'aiello': 350, 'grin': 4033, 'abigail': 154, 'ruth': 7651, 'werner': 9747, 'wu': 9936, 'stepmother': 8510, 'marisa': 5528, 'tomei': 9103, 'strung': 8608, 'internal': 4725, 'dragging': 2788, 'satanic': 7717, 'elected': 2980, 'kei': 4978, 'recurring': 7241, 'instruments': 4689, 'kali': 4951, 'nightmarish': 6089, 'macmurray': 5440, 'basil': 860, 'tramp': 9182, 'apologies': 560, 'headache': 4209, 'orleans': 6316, 'officials': 6241, 'neo': 6048, 'realist': 7191, 'neglected': 6038, 'akin': 365, 'jannings': 4834, 'evelyn': 3173, 'pows': 6811, 'chest': 1615, 'sensual': 7893, 'preach': 6822, 'aboard': 159, 'firode': 3526, 'ample': 460, 'napoleon': 5990, 'understandably': 9348, 'fashions': 3389, 'bonanza': 1109, 'neighbours': 6042, 'las': 5122, 'nolan': 6109, 'perky': 6562, 'registered': 7280, 'madsen': 5448, 'epics': 3119, 'raiders': 7104, 'ark': 614, 'sustained': 8778, 'concrete': 1957, 'toolbox': 9118, 'infidelity': 4623, 'foxes': 3679, 'communication': 1885, 'turtle': 9287, '1967': 53, 'insert': 4662, 'mo': 5811, 'supremacy': 8736, 'authors': 756, 'saturated': 7726, 'ninety': 6094, 'overtly': 6369, 'composition': 1929, 'sematary': 7876, 'watcher': 9686, 'studying': 8619, 'carell': 1430, 'oblivion': 6187, 'artistry': 647, 'shelly': 8008, 'gielgud': 3875, 'booze': 1130, 'florence': 3584, 'provocative': 6996, 'dietrich': 2608, 'pretends': 6872, 'raider': 7103, 'sunset': 8712, 'bench': 954, 'consumed': 2019, 'jews': 4874, 'holocaust': 4345, 'goo': 3945, 'ranma': 7135, 'compassionate': 1901, 'isabelle': 4792, 'cocktail': 1799, 'click': 1746, 'clunker': 1788, 'jodie': 4884, 'persuade': 6577, 'thereof': 8982, 'closure': 1775, 'behaves': 926, 'suggesting': 8689, 'del': 2443, 'regrets': 7282, 'krishna': 5066, 'coup': 2138, 'serbs': 7910, 'clumsily': 1786, 'suzanne': 8780, 'kinnear': 5028, 'invention': 4752, 'liner': 5282, 'snippets': 8253, 'waterfall': 9692, 'tin': 9067, 'compromise': 1935, 'demonicus': 2475, 'unsympathetic': 9421, 'sabrina': 7655, 'pets': 6590, 'bullock': 1294, 'visitor': 9582, 'zorro': 9998, 'delon': 2462, 'botched': 1144, 'davidson': 2365, 'substantial': 8651, 'mocking': 5816, 'dish': 2683, 'schwarzenegger': 7771, 'rescued': 7395, 'virtue': 9570, 'moonstruck': 5862, 'kinky': 5027, 'berenger': 966, 'wally': 9635, '1953': 43, 'mart': 5547, 'zealand': 9982, 'classified': 1723, 'soderbergh': 8270, 'oddball': 6219, 'centre': 1521, 'impending': 4532, 'percent': 6544, 'stumble': 8622, 'maximum': 5603, 'sites': 8151, 'pia': 6624, 'caretaker': 1432, 'competently': 1907, 'pirates': 6649, 'ebay': 2926, 'dolph': 2745, 'rupert': 7640, 'categories': 1483, 'neglect': 6037, 'port': 6763, 'transformations': 9188, 'sexes': 7948, 'hopper': 4379, 'longing': 5351, 'flower': 3588, 'gladiator': 3898, 'limbs': 5271, 'substitute': 8652, 'meryl': 5693, 'illustrates': 4505, 'lambs': 5097, 'transformers': 9190, 'distraught': 2708, 'bsg': 1265, 'caprica': 1408, 'collecting': 1823, 'discernible': 2662, 'grisly': 4038, 'meadows': 5622, 'shaggy': 7963, 'pulse': 7020, 'aunts': 743, 'denmark': 2486, 'indifferent': 4601, 'dahmer': 2306, 'granger': 3994, 'gruner': 4056, 'nemesis': 6047, 'denial': 2482, 'sonny': 8302, 'postman': 6796, 'gino': 3887, 'giovanna': 3888, 'employment': 3035, 'ossessione': 6323, 'monastery': 5837, 'wendy': 9740, 'shah': 7964, 'terrain': 8923, 'che': 1587, 'bolivia': 1103, 'toro': 9131, 'cringed': 2213, 'tracey': 9161, 'visitors': 9583, 'acquired': 226, 'generate': 3833, 'calibre': 1357, 'zoe': 9991, 'doolittle': 2758, 'gandolfini': 3791, 'muslims': 5954, 'unwittingly': 9427, 'token': 9092, 'askey': 662, 'keanu': 4971, 'kornbluth': 5061, 'mabel': 5432, '1920s': 18, 'recruits': 7240, 'herman': 4264, 'robbers': 7537, 'housing': 4409, 'zodiac': 9990, 'lommel': 5342, 'cowboys': 2160, 'detached': 2561, 'thankless': 8952, 'needing': 6031, 'censorship': 1516, 'cheryl': 1613, 'waqt': 9651, 'fundamental': 3751, 'northam': 6131, 'flute': 3594, 'obscene': 6190, 'artemisia': 641, 'tassi': 8861, 'manufactured': 5513, 'ogre': 6245, 'panahi': 6428, 'offside': 6243, '98': 147, 'irresistible': 4785, 'gabby': 3771, 'payne': 6511, 'scanners': 7745, 'cyborgs': 2295, 'bombing': 1107, 'insects': 4661, 'outdoor': 6337, 'predecessor': 6830, 'zentropa': 9985, 'europa': 3165, 'andrei': 478, 'tarkovsky': 8857, 'wodehouse': 9860, 'merry': 5692, 'cunning': 2270, 'impose': 4542, 'opener': 6274, 'officially': 6240, 'yuma': 9979, 'unnecessarily': 9404, 'grandpa': 3992, 'depardieu': 2498, 'flew': 3568, 'eagle': 2901, 'tintin': 9068, 'sickness': 8083, 'mpaa': 5918, 'arrest': 630, 'chandler': 1547, 'lundgren': 5417, 'stalks': 8447, 'succession': 8670, 'sho': 8029, 'gackt': 3774, 'troopers': 9256, 'fenton': 3445, 'naschy': 5996, 'floriane': 3585, 'animators': 503, 'cherish': 1612, 'parsons': 6457, 'quincy': 7076, 'gram': 3986, 'je': 4846, 'aime': 352, 'veronica': 9510, '250': 111, 'gypo': 4091, 'bfg': 990, 'brendan': 1211, 'gung': 4080, 'kriemhild': 5064, 'hagen': 4103, 'visconti': 9574, 'frantic': 3697, 'output': 6345, 'pornography': 6762, 'descends': 2522, 'indulge': 4606, 'hare': 4160, 'sought': 8322, 'bogdanovich': 1098, 'interplay': 4728, 'seventh': 7940, 'attendant': 721, 'mockumentary': 5817, 'gamera': 3787, 'lamarr': 5096, 'pedro': 6527, 'nacho': 5978, 'anton': 533, 'newcombe': 6066, 'sayuri': 7740, 'steamy': 8501, 'aaron': 149, 'gap': 3797, 'battlestar': 876, 'galactica': 3782, 'annoyance': 514, 'amuse': 462, 'disappoints': 2656, 'ustinov': 9455, 'trendy': 9229, 'highway': 4291, 'yikes': 9961, 'mordrid': 5871, 'denver': 2492, 'harron': 4171, 'sammo': 7691, 'angelo': 487, 'cristina': 2219, 'binoche': 1013, 'ada': 245, 'actuality': 242, 'spray': 8416, 'alliance': 406, 'skinned': 8169, 'bounce': 1153, 'excessively': 3220, 'playful': 6688, 'corridors': 2114, 'wan': 9640, 'admirably': 270, 'fiancée': 3458, 'trish': 9249, 'hobgoblins': 4330, 'schneider': 7768, 'fated': 3397, '1943': 34, 'aircraft': 358, 'abu': 178, 'gospel': 3962, 'fetish': 3451, 'rao': 7138, 'btk': 1266, 'krueger': 5068, 'guevara': 4068, 'dross': 2838, 'stakes': 8442, 'iowa': 4769, 'sissy': 8144, 'tucci': 9273, 'burakov': 1303, 'thai': 8946, 'amin': 453, 'beetle': 913, 'minion': 5756, 'pasteur': 6486, 'joys': 4913, 'govinda': 3970, 'prem': 6843, 'randolph': 7126, 'saxon': 7736, 'delia': 2445, 'achilles': 221, 'hartnett': 4178, 'hark': 4162, 'candles': 1388, 'mj': 5810, 'edmund': 2947, 'wentworth': 9742, 'togar': 9089, 'barman': 844, 'puzzling': 7051, 'malta': 5484, 'protocol': 6985, 'flemming': 3565, 'nutshell': 6179, 'ahmad': 346, 'vinnie': 9559, 'dreyfuss': 2821, 'bloodshed': 1074, 'kells': 4982, 'sheila': 8004, 'watered': 9691, 'dyer': 2890, 'salman': 7682, 'gravity': 4007, 'blaise': 1038, 'scarecrows': 7748, 'icons': 4467, '64': 134, 'beckinsale': 903, 'conroy': 1992, 'pasolini': 6473, 'gadget': 3775, 'jed': 4850, 'arjun': 613, 'kabei': 4950, 'vivah': 9589, 'astronauts': 697, 'slackers': 8180, 'giamatti': 3871, 'pinjar': 6645, 'depalma': 2497, 'ae': 303, 'palermo': 6419, 'lensman': 5208, 'hackenstein': 4096, 'azumi': 789, 'iris': 4777, 'tolstoy': 9098}


BoW train dimension
[[0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]
 ...
 [0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]]

# Look at the shape of the obtained array
print("Shape of bow_train_reduced_vectors")
print(bow_train_splt.shape)

Shape of bow_train_reduced_vectors
(10000, 10000)

# Transform the validation data
vectorizer_val_splt = CountVectorizer(max_features=10000)
bow_val_splt = vectorizer_val_splt.fit_transform(val_texts)
val_splt_features_names = vectorizer_val_splt.get_feature_names()

print("\n\nTrain reduced features names")
print(val_splt_features_names)

print("\n\nVocabulary")
print(vectorizer_val_splt.vocabulary_)

bow_val_splt = bow_val_splt.toarray()
print("\n\nBow train reduced vectors")
print(bow_val_splt)

print("\n\nBoW validation shape")
print(bow_val_splt.shape)

Train reduced features names
['00', '000', '01', '10', '100', '101', '11', '11th', '12', '13', '13th', '14', '15', '16', '17', '17th', '18', '1890', '1894', '19', '1912', '1915', '1917', '1920', '1920s', '1922', '1928', '1929', '1930', '1930s', '1933', '1934', '1935', '1936', '1939', '1940', '1940s', '1942', '1943', '1944', '1945', '1946', '1948', '1949', '1950', '1950s', '1951', '1952', '1953', '1954', '1955', '1956', '1958', '1959', '1960', '1960s', '1961', '1962', '1965', '1966', '1967', '1968', '1969', '1970', '1970s', '1971', '1972', '1973', '1974', '1975', '1976', '1977', '1978', '1979', '1980', '1980s', '1981', '1982', '1983', '1984', '1985', '1986', '1987', '1988', '1989', '1990', '1990s', '1991', '1992', '1993', '1994', '1995', '1996', '1997', '1998', '1999', '19th', '1st', '20', '200', '2000', '2001', '2002', '2003', '2004', '2005', '2006', '2007', '2008', '20s', '20th', '21', '21st', '22', '23', '24', '25', '27', '28', '2d', '2nd', '30', '300', '3000', '30s', '31', '345', '35', '3d', '3rd', '40', '40s', '43', '45', '48', '50', '500', '50s', '60', '60s', '63', '66', '69', '6th', '70', '70s', '73', '75', '80', '80s', '85', '86', '90', '90s', '95', '97', '98', '99', 'aardman', 'aaron', 'abandon', 'abandoned', 'abby', 'abc', 'abhorrent', 'abilities', 'ability', 'able', 'aboard', 'aborigine', 'aborigines', 'abound', 'about', 'above', 'abraham', 'abrupt', 'abruptly', 'absence', 'absent', 'absolute', 'absolutely', 'absorbed', 'absorbing', 'abstract', 'absurd', 'absurdity', 'absurdly', 'abuse', 'abused', 'abysmal', 'academy', 'accent', 'accents', 'accept', 'acceptable', 'acceptance', 'accepted', 'accepting', 'accepts', 'access', 'accident', 'accidentally', 'acclaimed', 'accompanied', 'accompanying', 'accomplished', 'accomplishment', 'according', 'account', 'accounts', 'accuracy', 'accurate', 'accused', 'ace', 'achieve', 'achieved', 'achievement', 'achieves', 'achieving', 'acid', 'acknowledge', 'acquaintances', 'acquired', 'across', 'act', 'acted', 'acting', 'action', 'actions', 'active', 'activist', 'activities', 'activity', 'actor', 'actors', 'actress', 'actresses', 'acts', 'actual', 'actuality', 'actually', 'ad', 'adam', 'adams', 'adaptation', 'adaptations', 'adapted', 'adaption', 'add', 'added', 'addicted', 'addiction', 'adding', 'addition', 'additional', 'additionally', 'address', 'addressed', 'addresses', 'addressing', 'adds', 'adeline', 'adequate', 'admirable', 'admirably', 'admiration', 'admire', 'admired', 'admirer', 'admirers', 'admit', 'admits', 'admitted', 'admittedly', 'adolescent', 'adopt', 'adopted', 'adorable', 'adore', 'adored', 'adrian', 'adult', 'adulterous', 'adultery', 'adulthood', 'adults', 'advance', 'advanced', 'advances', 'advantage', 'adventure', 'adventures', 'adversity', 'advertised', 'advertisement', 'advertising', 'advice', 'advise', 'advised', 'adviser', 'advocate', 'aesthetic', 'aesthetically', 'affair', 'affairs', 'affect', 'affected', 'affecting', 'affection', 'affects', 'affinity', 'affirmative', 'affleck', 'afflicted', 'affluent', 'afford', 'aforementioned', 'afraid', 'africa', 'african', 'after', 'aftermath', 'afternoon', 'afterwards', 'again', 'against', 'agatha', 'age', 'aged', 'agency', 'agenda', 'agent', 'agents', 'ages', 'aggressive', 'aging', 'ago', 'agony', 'agree', 'agreed', 'agrees', 'ah', 'ahab', 'ahead', 'aid', 'aided', 'aids', 'aiello', 'aim', 'aimed', 'aiming', 'aimless', 'ain', 'air', 'aircraft', 'aired', 'airing', 'airplane', 'airport', 'aisle', 'ajax', 'ajay', 'aka', 'akin', 'akshay', 'al', 'ala', 'alan', 'alas', 'alba', 'albeit', 'albert', 'album', 'albums', 'alcohol', 'alec', 'alekos', 'alert', 'alex', 'alexander', 'alexis', 'alfred', 'ali', 'alibi', 'alice', 'alicia', 'alien', 'alienation', 'alienator', 'aliens', 'alike', 'alimony', 'alison', 'alive', 'all', 'allan', 'alleged', 'allegory', 'allen', 'alley', 'alliance', 'allow', 'allowed', 'allowing', 'allows', 'allure', 'allusions', 'ally', 'allyson', 'almost', 'alok', 'alone', 'along', 'alongside', 'alot', 'alpha', 'already', 'alright', 'also', 'alter', 'altering', 'alternate', 'alternately', 'alternates', 'alternating', 'alternative', 'although', 'altman', 'altogether', 'alvin', 'always', 'am', 'amanda', 'amateur', 'amateurish', 'amazed', 'amazing', 'amazingly', 'amazon', 'ambiance', 'ambiguity', 'ambiguous', 'ambition', 'ambitious', 'america', 'american', 'americans', 'amiable', 'amid', 'amidst', 'amitabh', 'amnesia', 'amok', 'among', 'amongst', 'amoral', 'amos', 'amount', 'amounts', 'amphibulos', 'ample', 'amrita', 'amsterdam', 'amuse', 'amused', 'amusement', 'amusing', 'amusingly', 'amy', 'an', 'anal', 'analog', 'analogy', 'analysis', 'analyze', 'anarene', 'anastasia', 'anchor', 'anchored', 'anchorman', 'ancient', 'and', 'anderson', 'andre', 'andrea', 'andreeff', 'andrew', 'andrews', 'android', 'andy', 'angel', 'angela', 'angeles', 'angelina', 'angels', 'anger', 'angered', 'angie', 'angle', 'angles', 'anglo', 'angry', 'angst', 'anguish', 'anguished', 'anil', 'animal', 'animals', 'animated', 'animation', 'anime', 'aniston', 'anita', 'ann', 'anna', 'annamarie', 'anne', 'annie', 'announced', 'announcement', 'announcer', 'announces', 'annoyance', 'annoyed', 'annoying', 'annoyingly', 'annoys', 'annual', 'anonymous', 'another', 'answer', 'answered', 'answers', 'antagonist', 'anthology', 'anthony', 'anthropologist', 'anti', 'anticipated', 'anticipation', 'antics', 'antiques', 'anton', 'antonietta', 'antonio', 'antonioni', 'antwone', 'anupam', 'anxiety', 'anxious', 'any', 'anybody', 'anyhow', 'anymore', 'anyone', 'anything', 'anytime', 'anyway', 'anyways', 'anywhere', 'apart', 'apartment', 'apathetic', 'apathy', 'ape', 'apes', 'apocalypse', 'apocalyptic', 'apologies', 'apologize', 'appalled', 'appalling', 'appallingly', 'apparent', 'apparently', 'appeal', 'appealing', 'appeals', 'appear', 'appearance', 'appearances', 'appeared', 'appearing', 'appears', 'applaud', 'apple', 'applied', 'appreciate', 'appreciated', 'appreciating', 'appreciation', 'approach', 'approaches', 'approaching', 'appropriate', 'appropriately', 'approval', 'april', 'apt', 'arab', 'aragorn', 'arc', 'archaeological', 'archer', 'architect', 'architecture', 'arcs', 'ardala', 'are', 'area', 'areas', 'aren', 'arguably', 'argue', 'argued', 'argument', 'arguments', 'ariel', 'aristocrats', 'arkin', 'arly', 'arm', 'armed', 'armies', 'armor', 'arms', 'army', 'arnold', 'around', 'arquette', 'arranged', 'arrangement', 'array', 'arrested', 'arrival', 'arrive', 'arrived', 'arrives', 'arrogance', 'arrogant', 'arrow', 'arrows', 'art', 'artemisia', 'arthur', 'articulate', 'artificial', 'artificially', 'artist', 'artistic', 'artists', 'arts', 'artsy', 'artwork', 'arty', 'as', 'ash', 'ashamed', 'ashes', 'ashraf', 'asia', 'asian', 'aside', 'ask', 'asked', 'asking', 'asks', 'asleep', 'aspect', 'aspects', 'aspires', 'aspiring', 'ass', 'assassin', 'assassinate', 'assassination', 'assault', 'assed', 'assembled', 'assertion', 'assessment', 'asset', 'assets', 'assigned', 'assignment', 'assist', 'assistance', 'assistant', 'assistants', 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'skits', 'skull', 'sky', 'slam', 'slams', 'slap', 'slapping', 'slapstick', 'slasher', 'slater', 'slave', 'slaves', 'sleazy', 'sleep', 'sleepaway', 'sleeper', 'sleeping', 'sleeps', 'sleepwalkers', 'sleeve', 'sleuth', 'slew', 'slice', 'slick', 'slide', 'sliding', 'slight', 'slightest', 'slightly', 'slim', 'slimy', 'slip', 'slipped', 'slips', 'slipstream', 'sloane', 'sloppy', 'sloth', 'slow', 'slower', 'slowly', 'slug', 'slum', 'sly', 'small', 'smaller', 'smallest', 'smarmy', 'smart', 'smartly', 'smash', 'smashed', 'smells', 'smile', 'smiles', 'smiling', 'smith', 'smoke', 'smoking', 'smooth', 'smuggling', 'snake', 'snakes', 'snappy', 'snatch', 'sneak', 'snipe', 'sniper', 'snipes', 'snippets', 'snitch', 'snl', 'snob', 'snow', 'snuff', 'so', 'soap', 'sober', 'soccer', 'social', 'socialist', 'societal', 'society', 'sock', 'socks', 'soderbergh', 'soft', 'softcore', 'soha', 'sol', 'sold', 'soldier', 'soldiers', 'sole', 'solely', 'soles', 'solid', 'solitary', 'solitude', 'sollett', 'solo', 'solution', 'solutions', 'solvang', 'solve', 'solved', 'some', 'somebody', 'someday', 'somehow', 'someone', 'something', 'somethings', 'sometime', 'sometimes', 'somewhat', 'somewhere', 'son', 'song', 'songs', 'sonia', 'sonic', 'sons', 'sony', 'soon', 'sooner', 'sophia', 'sophie', 'sophisticated', 'sophistication', 'sophomore', 'sordid', 'sorry', 'sort', 'sorts', 'soul', 'souls', 'sound', 'sounded', 'sounding', 'sounds', 'soundstage', 'soundtrack', 'soup', 'source', 'sources', 'south', 'southern', 'soviet', 'sox', 'soylent', 'space', 'spaceship', 'spaceships', 'spacey', 'spade', 'spaghetti', 'spanish', 'spare', 'sparing', 'spark', 'sparked', 'sparkle', 'sparkles', 'sparkling', 'spawn', 'speak', 'speaking', 'speaks', 'spears', 'special', 'specially', 'specials', 'species', 'specific', 'specifically', 'spectacle', 'spectacular', 'spectrum', 'speech', 'speeches', 'speed', 'speeding', 'spell', 'spells', 'spencer', 'spend', 'spending', 'spends', 'spent', 'spider', 'spiderman', 'spielberg', 'spies', 'spike', 'spilling', 'spin', 'spinal', 'spine', 'spirit', 'spirited', 'spiritual', 'spit', 'spite', 'splatter', 'splendid', 'split', 'splitting', 'spock', 'spoil', 'spoiled', 'spoiler', 'spoilers', 'spoiling', 'spoke', 'spoken', 'spontaneous', 'spoof', 'spoofing', 'spoofs', 'spooky', 'sport', 'sports', 'spot', 'spotlight', 'spots', 'spouse', 'spread', 'spree', 'spring', 'springer', 'springs', 'springsteen', 'springwood', 'spy', 'squad', 'squalor', 'squandered', 'square', 'squeamish', 'squeeze', 'ss', 'st', 'stabbed', 'stabbing', 'stability', 'staff', 'stage', 'staged', 'stages', 'stagnant', 'stairs', 'stale', 'stalked', 'stalker', 'stalks', 'stallone', 'stamp', 'stan', 'stance', 'stand', 'standard', 'standards', 'standing', 'standout', 'stands', 'standup', 'stanley', 'stanwyck', 'staple', 'star', 'stare', 'stares', 'stargate', 'staring', 'stark', 'starr', 'starred', 'starring', 'stars', 'start', 'started', 'starters', 'starting', 'startled', 'startling', 'starts', 'starving', 'state', 'stated', 'statement', 'statements', 'states', 'static', 'stating', 'station', 'stations', 'statue', 'stature', 'status', 'stay', 'stayed', 'staying', 'stays', 'steady', 'steal', 'stealing', 'steals', 'steam', 'steamy', 'steel', 'steele', 'steer', 'steiner', 'stella', 'stellar', 'step', 'stephen', 'stepmother', 'stepping', 'steps', 'stepsisters', 'stereo', 'stereotype', 'stereotypes', 'stereotypical', 'stereotyping', 'stern', 'steve', 'steven', 'stevens', 'stew', 'stewart', 'stick', 'sticking', 'sticks', 'stiff', 'stiles', 'still', 'stiller', 'stilted', 'sting', 'stink', 'stinker', 'stinks', 'stock', 'stole', 'stolen', 'stoltz', 'stomach', 'stone', 'stones', 'stood', 'stooges', 'stop', 'stopped', 'stopping', 'stops', 'store', 'stores', 'storey', 'stories', 'storm', 'story', 'storyboard', 'storyline', 'storytelling', 'straight', 'straightforward', 'strained', 'stranded', 'strange', 'strangely', 'stranger', 'strangers', 'strangler', 'strategy', 'stratten', 'stray', 'streak', 'stream', 'streep', 'street', 'streets', 'streetwise', 'streisand', 'strength', 'stress', 'stretch', 'stretched', 'strickland', 'strict', 'strictly', 'strike', 'strikes', 'striking', 'string', 'strings', 'strip', 'stripper', 'stripping', 'strive', 'strives', 'stroke', 'stroker', 'strong', 'stronger', 'strongest', 'strongly', 'struck', 'structure', 'struggle', 'struggled', 'struggles', 'struggling', 'strummer', 'strut', 'strutting', 'stuart', 'stuck', 'stud', 'student', 'students', 'studied', 'studies', 'studio', 'studios', 'study', 'studying', 'stuff', 'stumbled', 'stumbles', 'stunk', 'stunned', 'stunning', 'stunt', 'stunts', 'stupid', 'stupider', 'stupidest', 'stupidity', 'stupidly', 'style', 'styles', 'stylish', 'stylistic', 'stylized', 'suave', 'sub', 'subject', 'subjected', 'subjects', 'submarine', 'subplot', 'subplots', 'subsequent', 'subsequently', 'substance', 'substantial', 'subtitles', 'subtle', 'subtlety', 'subtly', 'suburban', 'subway', 'succeed', 'succeeded', 'succeeds', 'success', 'successes', 'successful', 'successfully', 'succession', 'such', 'suck', 'sucked', 'sucking', 'sucks', 'sudden', 'suddenly', 'sue', 'suffer', 'suffered', 'suffering', 'suffers', 'suffice', 'sufficient', 'sugar', 'suggest', 'suggested', 'suggesting', 'suggestion', 'suggestive', 'suggests', 'suicide', 'suit', 'suitable', 'suitably', 'suited', 'suitors', 'suits', 'sullivan', 'sum', 'summarize', 'summary', 'summation', 'summer', 'summoned', 'sums', 'sun', 'sunday', 'sunk', 'sunny', 'sunset', 'sunshine', 'super', 'superb', 'superbly', 'superficial', 'superhero', 'superior', 'superlative', 'superman', 'supermarionation', 'supermarket', 'supernatural', 'superpowers', 'superstar', 'supplies', 'supply', 'support', 'supported', 'supporting', 'suppose', 'supposed', 'supposedly', 'suppress', 'supreme', 'supremely', 'sure', 'surely', 'surf', 'surface', 'surfing', 'surgeon', 'surgery', 'surprise', 'surprised', 'surprises', 'surprising', 'surprisingly', 'surreal', 'surround', 'surrounded', 'surrounding', 'surroundings', 'survival', 'survive', 'survived', 'survives', 'surviving', 'survivor', 'survivors', 'susan', 'suspect', 'suspected', 'suspects', 'suspend', 'suspense', 'suspenseful', 'suspension', 'suspicion', 'suspicious', 'sustain', 'sutherland', 'suzanne', 'suzette', 'swanson', 'sway', 'swayze', 'swear', 'swearing', 'swedish', 'sweeps', 'sweet', 'sweetheart', 'swept', 'swift', 'swim', 'swimming', 'swing', 'swinging', 'switch', 'switched', 'swoon', 'sword', 'sybil', 'sydney', 'sydow', 'sylvia', 'symbol', 'symbolic', 'symbolism', 'sympathetic', 'sympathise', 'sympathize', 'sympathy', 'sync', 'syndrome', 'synopsis', 'system', 'table', 'tables', 'taboo', 'tack', 'tackle', 'tacky', 'tad', 'taffy', 'tag', 'tail', 'tailor', 'takashi', 'take', 'takechi', 'taken', 'takes', 'taking', 'tale', 'talent', 'talented', 'talentless', 'talents', 'tales', 'talespin', 'talk', 'talked', 'talkie', 'talkies', 'talking', 'talks', 'tall', 'tame', 'tangled', 'tango', 'tanks', 'tanya', 'tap', 'tape', 'taped', 'tapes', 'tapping', 'tara', 'tarantino', 'target', 'targeted', 'targets', 'tarzan', 'tashan', 'task', 'taste', 'tasteful', 'tastes', 'tasty', 'taught', 'taut', 'tax', 'taxi', 'taylor', 'tcm', 'tea', 'teach', 'teacher', 'teachers', 'teaching', 'team', 'teaming', 'tear', 'tearjerker', 'tears', 'tech', 'technical', 'technically', 'technicolor', 'technique', 'techniques', 'techno', 'technological', 'technology', 'ted', 'teddy', 'tedious', 'tediously', 'teen', 'teenage', 'teenager', 'teenagers', 'teens', 'teeth', 'tel', 'telephone', 'television', 'tell', 'telling', 'tells', 'temple', 'tempted', 'ten', 'tenant', 'tend', 'tendency', 'tender', 'tends', 'tennis', 'tense', 'tension', 'tent', 'tepid', 'teresa', 'term', 'terminator', 'terms', 'terrible', 'terribly', 'terrific', 'terrifically', 'terrifying', 'territory', 'terror', 'terrorism', 'terrorists', 'terry', 'tess', 'test', 'testament', 'tested', 'testing', 'tet', 'texas', 'text', 'textile', 'thade', 'thai', 'thailand', 'than', 'thank', 'thankfully', 'thanks', 'that', 'thats', 'the', 'theater', 'theaters', 'theatre', 'theatres', 'theatrical', 'theft', 'their', 'theirs', 'thelma', 'them', 'theme', 'themed', 'themes', 'themselves', 'then', 'theo', 'theories', 'theory', 'therapy', 'there', 'therefore', 'therein', 'thereof', 'these', 'thespian', 'thespians', 'they', 'thhe', 'thick', 'thief', 'thieves', 'thin', 'thing', 'things', 'think', 'thinking', 'thinks', 'thinly', 'third', 'thirties', 'thirty', 'this', 'tho', 'thomas', 'thompson', 'thornton', 'thoroughly', 'those', 'though', 'thought', 'thoughtful', 'thoughts', 'thousand', 'thousands', 'threads', 'threat', 'threatened', 'threatening', 'threats', 'three', 'threw', 'thrill', 'thrilled', 'thriller', 'thrillers', 'thrilling', 'thrills', 'throat', 'throne', 'through', 'throughout', 'throw', 'throwaway', 'throwing', 'thrown', 'throws', 'thru', 'thugs', 'thumbs', 'thunderbirds', 'thurman', 'thus', 'tia', 'tibet', 'tibetan', 'tick', 'ticket', 'tickets', 'tie', 'tied', 'tierney', 'ties', 'tiffany', 'tiger', 'tight', 'till', 'tilly', 'tim', 'timberlake', 'time', 'timed', 'timeless', 'timely', 'times', 'timid', 'timing', 'timmy', 'timothy', 'tina', 'tingler', 'tinted', 'tiny', 'tip', 'tire', 'tired', 'tiresome', 'titanic', 'title', 'titled', 'titles', 'titular', 'to', 'tobias', 'today', 'todd', 'toe', 'together', 'toilet', 'token', 'tokyo', 'told', 'tolerable', 'tolerance', 'tolkien', 'tom', 'tomatoes', 'tomb', 'tomba', 'tomei', 'tommy', 'tomorrow', 'ton', 'tone', 'toned', 'tongue', 'tonight', 'tons', 'tony', 'too', 'took', 'tool', 'tools', 'tooth', 'toots', 'top', 'topic', 'topics', 'topless', 'tops', 'torment', 'tormented', 'torments', 'torn', 'toronto', 'torrance', 'torrence', 'torture', 'tortured', 'torturing', 'toss', 'tossed', 'total', 'totally', 'toto', 'touch', 'touched', 'touches', 'touching', 'tough', 'toughness', 'toupee', 'tour', 'tourist', 'tourists', 'tourneur', 'toward', 'towards', 'tower', 'towers', 'town', 'townsend', 'toxic', 'toy', 'toys', 'trace', 'track', 'trackers', 'tracking', 'tracks', 'tracy', 'trade', 'trademark', 'tradition', 'traditional', 'traffic', 'trafficking', 'tragedy', 'tragic', 'tragically', 'trail', 'trailer', 'trailers', 'train', 'trained', 'training', 'traitor', 'traits', 'tramp', 'trance', 'transcend', 'transcends', 'transfer', 'transferred', 'transformation', 'transformed', 'transition', 'translate', 'translated', 'translation', 'transmitted', 'transparent', 'transport', 'transportation', 'transported', 'transvestite', 'trap', 'trapped', 'traps', 'trash', 'trashed', 'trashy', 'trauma', 'traumatic', 'travel', 'traveling', 'travelling', 'travelogue', 'travels', 'travesty', 'travolta', 'treasure', 'treasury', 'treat', 'treated', 'treating', 'treatment', 'treats', 'trebor', 'tree', 'trees', 'trek', 'trelkovsky', 'tremendous', 'tremendously', 'tremors', 'trend', 'trendy', 'trent', 'trial', 'trials', 'triangle', 'tribal', 'tribe', 'tribes', 'tribute', 'trick', 'tricked', 'tricks', 'trident', 'tried', 'trier', 'tries', 'trigger', 'trilogy', 'trina', 'trinity', 'trio', 'trip', 'tripe', 'triple', 'tripping', 'trippy', 'trips', 'trite', 'triton', 'triumph', 'triumphant', 'trivia', 'trivial', 'trodden', 'trois', 'trojan', 'troma', 'troopers', 'troops', 'trotta', 'trouble', 'troubled', 'troubles', 'troublesome', 'truck', 'true', 'truely', 'truffaut', 'truly', 'truman', 'trumpeter', 'trunk', 'trust', 'trusted', 'truth', 'truthful', 'truthfully', 'truths', 'try', 'trying', 'tub', 'tube', 'tucker', 'tumbling', 'tune', 'tunes', 'tung', 'tunnel', 'turd', 'turgid', 'turkey', 'turkeys', 'turmoil', 'turn', 'turned', 'turner', 'turning', 'turns', 'tv', 'twelve', 'twenty', 'twice', 'twilight', 'twin', 'twins', 'twist', 'twisted', 'twists', 'two', 'tycoon', 'tyler', 'type', 'typed', 'types', 'typical', 'typically', 'typing', 'uber', 'ugh', 'ugly', 'uh', 'uk', 'ultimate', 'ultimately', 'ultra', 'um', 'uma', 'un', 'unable', 'unanswered', 'unaware', 'unbearable', 'unbeknownst', 'unbelievable', 'unbelievably', 'unborn', 'uncanny', 'uncle', 'uncomfortable', 'unconvincing', 'uncreative', 'uncredited', 'uncut', 'undeniably', 'under', 'underdeveloped', 'underdog', 'underground', 'underlying', 'underneath', 'underrated', 'understand', 'understandable', 'understandably', 'understanding', 'understands', 'understated', 'understatement', 'understood', 'undertones', 'underwater', 'underwear', 'underworld', 'undeveloped', 'undoubtedly', 'uneasy', 'unemployed', 'uneven', 'unexpected', 'unexpectedly', 'unexplained', 'unfair', 'unfaithful', 'unfold', 'unfolds', 'unforgettable', 'unfortunate', 'unfortunately', 'unfunny', 'unhappy', 'uniform', 'uniformly', 'uniforms', 'unimaginative', 'uninspired', 'unintentional', 'unintentionally', 'uninteresting', 'union', 'unique', 'unisol', 'unisols', 'unit', 'united', 'universal', 'universe', 'university', 'unknown', 'unless', 'unlikable', 'unlike', 'unlikeable', 'unlikely', 'unnatural', 'unnecessarily', 'unnecessary', 'unnerving', 'unnoticed', 'unoriginal', 'unpleasant', 'unprecedented', 'unpredictable', 'unrated', 'unravel', 'unreal', 'unrealistic', 'unrecognizable', 'unrelated', 'unremarkable', 'unremittingly', 'unresolved', 'unsatisfied', 'unsatisfying', 'unscathed', 'unseen', 'unsettling', 'unsolved', 'unspeakable', 'unsuccessful', 'unsure', 'unsuspecting', 'unsympathetic', 'untalented', 'unthinkable', 'unthoughtful', 'until', 'untimely', 'untrue', 'unusual', 'unusually', 'unveils', 'unwashed', 'unwatchable', 'unwilling', 'unwittingly', 'up', 'upa', 'upbeat', 'upbringing', 'upcoming', 'update', 'updated', 'updates', 'uplifting', 'upon', 'upper', 'ups', 'upset', 'upside', 'uptight', 'urban', 'urge', 'urgent', 'ursula', 'us', 'usa', 'use', 'used', 'useful', 'useless', 'user', 'uses', 'using', 'ustinov', 'usual', 'usually', 'utilized', 'utopia', 'utter', 'utterly', 'uwe', 'vacation', 'vader', 'vague', 'vaguely', 'vain', 'valentine', 'valerie', 'valette', 'valid', 'valley', 'value', 'values', 'vampire', 'vampires', 'van', 'vance', 'vanessa', 'vanishing', 'vanity', 'vapid', 'variation', 'varied', 'variety', 'various', 'vary', 'varying', 'vast', 'vastly', 'vaudeville', 'vault', 'vcr', 've', 'vega', 'vegas', 'vehicle', 'vehicles', 'vein', 'velvet', 'venantini', 'venantino', 'vengeance', 'venture', 'vera', 'verge', 'verhoeven', 'veronica', 'versa', 'verse', 'version', 'versions', 'versus', 'vertigo', 'very', 'veteran', 'veterans', 'vets', 'vhs', 'via', 'vibe', 'vibrancy', 'vibrant', 'vice', 'vices', 'vicious', 'vick', 'victim', 'victims', 'victor', 'victoria', 'victorian', 'victory', 'vida', 'video', 'videos', 'vienna', 'viet', 'vietnam', 'vietnamese', 'view', 'viewed', 'viewer', 'viewers', 'viewing', 'viewings', 'viewpoint', 'views', 'viggo', 'vigilance', 'vignettes', 'vijay', 'viking', 'vikings', 'vile', 'village', 'villain', 'villainess', 'villainous', 'villains', 'vince', 'vincent', 'vincenzo', 'vintage', 'violated', 'violence', 'violent', 'violently', 'virgin', 'virginia', 'virile', 'virtual', 'virtually', 'virtue', 'virus', 'visceral', 'visconti', 'visible', 'vision', 'visions', 'visit', 'visited', 'visiting', 'visits', 'visual', 'visually', 'visuals', 'vital', 'vittorio', 'vivacious', 'vivah', 'vivian', 'vivid', 'vlad', 'vocabulary', 'vocal', 'vocals', 'vodka', 'voice', 'voiced', 'voices', 'void', 'voight', 'vollins', 'volume', 'volunteer', 'vomit', 'von', 'voodoo', 'vote', 'voted', 'voters', 'vow', 'voyage', 'vs', 'vu', 'vulgar', 'vulnerability', 'vulnerable', 'wacky', 'waggoner', 'wagner', 'wai', 'waist', 'wait', 'waited', 'waiting', 'waitress', 'waits', 'wake', 'wakes', 'waking', 'wal', 'walk', 'walked', 'walken', 'walker', 'walking', 'walks', 'wall', 'wallace', 'wallet', 'walls', 'walsh', 'walt', 'walter', 'wan', 'wandering', 'wanders', 'wang', 'wanna', 'wannabe', 'want', 'wanted', 'wanting', 'wants', 'war', 'ward', 'warden', 'wardrobe', 'warfield', 'wargames', 'warm', 'warmed', 'warming', 'warmth', 'warn', 'warned', 'warner', 'warning', 'warns', 'warp', 'warped', 'warrant', 'warren', 'warrior', 'warriors', 'wars', 'wartime', 'was', 'wash', 'washed', 'washing', 'washington', 'wasn', 'waste', 'wasted', 'wastes', 'wasting', 'watch', 'watchable', 'watched', 'watches', 'watching', 'water', 'waterfall', 'waterfront', 'waters', 'watson', 'wave', 'waves', 'wax', 'way', 'wayne', 'ways', 'wayward', 'we', 'weak', 'weakest', 'weakness', 'weaknesses', 'wealth', 'wealthy', 'weapon', 'weapons', 'wear', 'wearing', 'wears', 'weary', 'weather', 'web', 'website', 'wedding', 'wee', 'weed', 'week', 'weekend', 'weeks', 'weight', 'weird', 'weirdo', 'weismuller', 'weissmuller', 'welcome', 'welcomed', 'well', 'weller', 'welles', 'wells', 'wenders', 'wendigo', 'wendy', 'went', 'were', 'weren', 'werewolf', 'werewolves', 'werner', 'wes', 'wesley', 'west', 'western', 'westerns', 'wet', 'whacked', 'whale', 'what', 'whatever', 'whats', 'whatsoever', 'wheel', 'wheelchair', 'wheezer', 'when', 'whenever', 'where', 'whereas', 'whereby', 'wherever', 'whether', 'whew', 'which', 'while', 'whilst', 'whim', 'whims', 'whimsical', 'whining', 'whiny', 'whip', 'whipped', 'whipping', 'whispered', 'white', 'who', 'whoever', 'whole', 'wholly', 'whom', 'whomever', 'whoopi', 'whore', 'whose', 'why', 'wicked', 'wide', 'widely', 'wider', 'widmark', 'widow', 'widowed', 'wielding', 'wife', 'wig', 'wilcox', 'wild', 'wilder', 'wilderness', 'wildly', 'will', 'william', 'williams', 'willie', 'willing', 'willingly', 'willis', 'wilson', 'wimpy', 'win', 'winchester', 'wind', 'window', 'windows', 'winds', 'wine', 'wing', 'wings', 'winkler', 'winner', 'winning', 'wins', 'winslet', 'winter', 'winters', 'wiped', 'wire', 'wisdom', 'wise', 'wiser', 'wish', 'wished', 'wishes', 'wishing', 'wit', 'witch', 'witchcraft', 'witches', 'witching', 'with', 'within', 'without', 'witless', 'witness', 'witnessed', 'witted', 'witty', 'wives', 'wizard', 'wolf', 'wolfe', 'woman', 'womanizing', 'women', 'won', 'wonder', 'wondered', 'wonderful', 'wonderfully', 'wondering', 'wonderland', 'wonders', 'wong', 'wont', 'woo', 'wood', 'wooden', 'woods', 'woody', 'word', 'words', 'wore', 'work', 'worked', 'worker', 'workers', 'working', 'workings', 'workout', 'works', 'world', 'worldly', 'worlds', 'worm', 'worms', 'worn', 'worried', 'worry', 'worse', 'worship', 'worst', 'worth', 'worthless', 'worthwhile', 'worthy', 'would', 'wouldn', 'wound', 'wounded', 'wow', 'wrap', 'wrapped', 'wrath', 'wreck', 'wrenching', 'wrestler', 'wrestlers', 'wrestling', 'wretched', 'wright', 'write', 'writer', 'writers', 'writes', 'writing', 'written', 'wrong', 'wrongly', 'wrote', 'wu', 'ww', 'ww2', 'wwe', 'wwi', 'wwii', 'www', 'xica', 'xp', 'ya', 'yacht', 'yadda', 'yakuza', 'yankee', 'yankovic', 'yard', 'yarn', 'yawn', 'yeah', 'year', 'years', 'yell', 'yelling', 'yellow', 'yep', 'yes', 'yesterday', 'yet', 'yeti', 'yikes', 'yokai', 'york', 'yorkers', 'yoshida', 'you', 'young', 'younger', 'youngest', 'your', 'yours', 'yourself', 'youth', 'youthful', 'youtube', 'yuck', 'yuk', 'yul', 'yum', 'zane', 'zany', 'zero', 'zeta', 'zizek', 'zodiac', 'zoe', 'zombie', 'zombies', 'zomcon', 'zone', 'zoo']


Vocabulary
{'we': 9718, 'could': 2102, 'still': 8534, 'use': 9459, 'black': 1073, 'even': 3150, 'today': 9070, 'imagine': 4523, 'the': 8946, 'role': 7616, 'of': 6302, 'assistant': 687, 'to': 9068, 'prime': 6947, 'minister': 5816, 'played': 6750, 'by': 1366, 'wonderful': 9878, 'hugh': 4411, 'laurie': 5156, 'is': 4827, 'sensational': 7914, 'as': 655, 'prince': 6949, 'george': 3796, 'and': 481, 'his': 4301, 'brilliant': 1256, 'love': 5383, 'episode': 3095, 'which': 9783, 'kenneth': 5007, 'connor': 1976, 'guest': 4039, 'stars': 8475, 'british': 1263, 'thespian': 8971, 'every': 3158, 'time': 9046, 'says': 7782, 'macbeth': 5448, 'two': 9301, 'thespians': 8972, 'do': 2714, 'silly': 8131, 'little': 5305, 'act': 224, 'ward': 9669, 'off': 6303, 'evil': 3168, 'it': 4839, 'funniest': 3711, 'things': 8980, 'that': 8944, 'you': 9974, 'will': 9821, 'see': 7881, 'course': 2119, 'none': 6185, 'this': 8988, 'brilliance': 1255, 'comedic': 1852, 'genius': 3786, 'be': 904, 'without': 9862, 'ben': 991, 'elton': 2995, 'richard': 7525, 'curtis': 2253, 'who': 9796, 'are': 608, 'also': 418, 'behind': 963, 'films': 3459, 'like': 5264, 'actually': 240, 'thin': 8978, 'blue': 1119, 'line': 5281, 'four': 3630, 'funny': 3712, 'almost': 409, 'too': 9095, 'good': 3919, 'for': 3586, 'television': 8897, 'humor': 4426, 'can': 1408, 'smart': 8244, 'sexy': 7981, 'all': 394, 'at': 713, 'one': 6352, 'was': 9691, 'hoping': 4366, 'last': 5133, 'night': 6155, 'on': 6349, 'saturday': 7770, 'live': 5308, 'would': 9916, 'pay': 6593, 'homage': 4337, 'background': 812, 'in': 4568, 'if': 4492, 'gang': 3742, 'snl': 8267, 'did': 2569, 'some': 8302, 'research': 7439, 'they': 8973, 'know': 5063, 'what': 9768, 'treasure': 9197, 'have': 4165, 'grace': 3951, 'their': 8953, 'stage': 8443, 'burt': 1342, 'kennedy': 5005, 'used': 9460, 'very': 9526, 'director': 2617, 'but': 1354, 'never': 6130, 'mess': 5754, 'not': 6206, 'only': 6356, 'does': 2725, 'film': 3453, 'look': 5354, 'cheap': 1615, 'most': 5950, 'battle': 895, 'scenes': 7797, 'lifted': 5252, 'from': 3687, 'far': 3347, 'superior': 8716, 'command': 1865, '1955': 50, 'footage': 3583, 'shot': 8082, 'years': 9960, 'previously': 6937, 'looks': 5357, 'more': 5931, 'contemporary': 2009, 'than': 8940, 'anything': 555, 'picture': 6699, 'few': 3420, 'action': 227, 'were': 9755, 'movie': 5977, 'confused': 1962, 'incompetent': 4593, 'looking': 5356, 'just': 4970, 'shoddy': 8062, 'rest': 7467, 'has': 4153, 'feel': 3394, 'bad': 818, 'student': 8617, 'budget': 1300, 'didn': 2570, 'seem': 7888, 'whole': 9798, 'lot': 5374, 'moves': 5976, 'acting': 226, 'part': 6539, 'either': 2967, 'over': 6443, 'top': 9101, 'ham': 4092, 'or': 6384, 'under': 9337, 'comatose': 1840, 'although': 426, 'julia': 4955, 'comes': 1855, 'better': 1023, 'cast': 1501, 'chock': 1661, 'full': 3703, 'annoying': 524, 'historical': 4304, 'inaccuracies': 4570, 'way': 9714, 'long': 5348, 're': 7223, 'going': 3902, 'make': 5492, 'boring': 1173, 'an': 469, 'hour': 4389, 'so': 8271, 'get': 3809, 'with': 9860, 'don': 2745, 'stretch': 8584, 'out': 6424, 'three': 9006, 'hours': 4390, 'want': 9664, 'about': 172, 'check': 1619, 'john': 4918, 'wayne': 9715, '1960': 54, 'version': 9522, 'stole': 8542, 'its': 4845, 'hard': 4132, 'believe': 974, 'took': 9096, 'six': 8176, 'producers': 6976, 'lousy': 5381, 'skip': 8193, 'whereas': 9778, 'boiled': 1141, 'detective': 2531, 'stories': 8557, 'raymond': 7221, 'chandler': 1575, 'cinema': 1702, 'fox': 3633, 'chicken': 1641, 'indeed': 4609, 'creating': 2156, 'modern': 5874, 'american': 445, 'genre': 3788, 'style': 8638, 'process': 6971, 'those': 8994, 'might': 5785, 'called': 1385, 'golden': 3909, 'age': 327, 'fiction': 3426, 'made': 5459, 'barely': 858, 'any': 550, 'impression': 4560, 'whatsoever': 9771, 'problem': 6964, 'books': 1161, 'agatha': 326, 'christie': 1685, 'dorothy': 2762, 'van': 9488, 'whose': 9804, 'work': 9893, 'based': 873, 'low': 5391, 'variety': 9496, 'sam': 7737, 'spade': 8351, 'philip': 6669, 'mean': 5660, 'streets': 8579, 'la': 5087, 'working': 9897, 'class': 1730, 'bars': 868, 'offices': 6320, 'wealthy': 9724, 'meet': 5690, 'sorts': 8330, 'exciting': 3199, 'dangers': 2302, 'violence': 9577, 'generally': 3777, 'fixed': 3504, 'location': 5327, 'scene': 7795, 'murder': 6003, 'usually': 9468, 'lavish': 5157, 'country': 2110, 'house': 4391, 'limited': 5274, 'investigating': 4793, 'clues': 1788, 'interviewing': 4766, 'suspects': 8762, 'static': 8489, 'procedure': 6966, 'plot': 6766, 'reduced': 7296, 'puzzle': 7110, 'br': 1208, 'much': 5987, 'ideological': 4484, 'else': 2993, 'dealing': 2353, 'society': 8278, 'hostile': 4385, 'change': 1577, 'movement': 5974, 'novels': 6225, 'recording': 7280, 'urban': 9453, 'reality': 7245, 'increasingly': 4605, 'moving': 5980, 'away': 790, 'centre': 1552, 'both': 1181, 'authority': 768, 'city': 1715, 'itself': 4846, 'up': 9438, 'into': 4769, 'ever': 3156, 'camps': 1406, 'another': 529, 'major': 5490, 'character': 1588, 'because': 928, 'cannot': 1422, 'answer': 530, 'crime': 2179, 'until': 9428, 'end': 3033, 'gain': 3733, 'access': 199, 'characters': 1594, 'motivations': 5960, 'emotions': 3016, 'being': 966, 'defined': 2404, 'solely': 8290, 'potential': 6853, 'need': 6098, 'unlike': 9393, 'anxious': 549, 'prejudice': 6897, 'ridden': 7532, 'private': 6959, 'eyes': 3289, 'simply': 8146, 'there': 8966, 'maybe': 5635, 'eccentric': 2923, 'try': 9271, 'period': 6639, 'jane': 4864, 'austen': 761, 'school': 7806, 'been': 938, 'successes': 8665, 'example': 3182, 'radical': 7153, 'queen': 7122, 'others': 6418, 'claude': 1737, 'english': 3053, 'speaking': 8363, 'world': 9901, 'really': 7251, 'classic': 1732, 'green': 3995, 'danger': 2299, 'works': 9900, 'pushes': 7105, 'form': 3608, 'parody': 6537, 'while': 9784, 'integrity': 4723, 'interest': 4747, 'mystery': 6038, 'before': 942, 'came': 1395, 'michael': 5774, 'curtiz': 2254, 'case': 1495, 'narrative': 6059, 'pure': 7089, 'repulsive': 7428, 'introduced': 4777, 'gives': 3851, 'number': 6236, 'reason': 7254, 'kill': 5027, 'him': 4288, 'he': 4177, 'murdered': 6004, 'seemingly': 7891, 'manner': 5523, 'suicide': 8690, 'locked': 5331, 'room': 7638, 'policemen': 6792, 'fall': 3324, 'hopelessly': 4364, 'bait': 825, 'philo': 6672, 'vance': 9489, 'gentleman': 3791, 'amateur': 433, 'neither': 6114, 'old': 6331, 'nor': 6192, 'fat': 3365, 'read': 7232, 'open': 6358, 'confines': 1953, 'eventually': 3155, 'solve': 8300, 'corpse': 2087, 'intellectual': 4725, 'interesting': 4749, 'unsatisfying': 9415, 'solutions': 8298, 'rarely': 7205, 'less': 5217, 'entertaining': 3080, 'comical': 1862, 'bits': 1069, 'business': 1348, 'isn': 4831, 'attempt': 729, 'image': 4515, 'perfect': 6626, 'where': 9777, 'brutal': 1287, 'sergeant': 7942, 'rough': 7655, 'suspect': 8760, 'no': 6168, 'protest': 7033, 'marks': 5563, 'considered': 1988, 'great': 3986, 'consistent': 1993, 'themes': 8959, 'evidence': 3165, 'artistic': 649, 'development': 2541, 'hollywood': 4332, 'greatest': 3988, 'here': 4247, 'story': 8559, 'mere': 5740, 'takes': 8822, 'idea': 4475, 'logical': 5337, 'extreme': 3283, 'abstract': 183, 'variation': 9494, 'source': 8340, 'series': 7944, 'lines': 5284, 'beautiful': 923, 'art': 642, 'deco': 2383, 'sets': 7961, 'glorious': 3875, 'camera': 1398, 'movements': 5975, 'suddenly': 8675, 'break': 1229, 'composition': 1920, 'glide': 3867, 'angle': 498, 'dead': 2346, 'life': 5247, 'treatment': 9202, 'appropriate': 594, 'refuses': 7316, 'realism': 7242, 'pattern': 6583, 'turns': 9290, 'hall': 4085, 'mirrors': 5829, 'central': 1551, 'brothers': 1280, 'original': 6403, 'borrowed': 1176, 'unsolved': 9419, 'mysteries': 6035, 'book': 1160, 'fantasy': 3345, 'nasty': 6066, 'rich': 7524, 'men': 5722, 'collect': 1819, 'shades': 7987, 'chinese': 1659, 'servants': 7949, 'ex': 3176, 'cons': 1979, 'turned': 9287, 'dog': 2727, 'loving': 5389, 'cops': 2073, 'man': 5507, 'drop': 2833, 'cruise': 2216, 'europe': 3143, 'knows': 5068, 'social': 8275, 'these': 8970, 'people': 6619, 'yet': 9967, 'association': 692, 'police': 6791, 'wasn': 9696, 'thinking': 8982, 'machine': 5450, 'william': 9822, 'powell': 6860, 'comedian': 1850, 'decade': 2368, 'humanity': 4420, 'climax': 1760, 'involving': 4805, 'vicious': 9537, 'dogs': 2729, 'attempted': 730, 'supposed': 8730, 'preventing': 6932, 'guilty': 4044, 'saw': 7779, 'couple': 2115, 'weeks': 9739, 'ago': 336, 'stuck': 8615, 'my': 6028, 'head': 4178, 'since': 8151, 'unfortunately': 9370, 'mediocre': 5684, 'documentary': 2721, 'true': 9258, 'beales': 907, 'had': 4067, 'through': 9016, 'dvd': 2884, 'bonus': 1156, 'material': 5614, 'search': 7855, 'web': 9732, 'fans': 3342, 'mention': 5730, 'edith': 2938, 'edie': 2934, 'themselves': 8960, 'suggestion': 8687, 'exploitative': 3252, 'exploitation': 3251, 'sense': 7915, 'word': 9890, 'effort': 2952, 'explain': 3239, 'how': 4397, 'condition': 1946, 'approach': 591, 'seems': 7892, 'turn': 9286, 'wait': 9636, 'say': 7780, 'something': 8307, 'outrageous': 6435, 'sound': 8333, 'release': 7347, 'poor': 6806, 'difficult': 2583, 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'earlier': 2901, 'disappointing': 2630, 'london': 5344, 'exactly': 3178, 'inspire': 4693, 'hope': 4359, 'me': 5657, 'first': 3489, 'however': 4400, 'feeling': 3395, 'different': 2580, 'college': 1823, 'girl': 3844, 'murders': 6009, 'bizarre': 1072, 'rather': 7210, 'wacky': 9631, 'flick': 3533, 'fun': 3706, 'watch': 9701, 'hate': 4157, 'throws': 9022, 'weird': 9741, 'ideas': 4479, 'script': 7843, 'manages': 5512, 'pull': 7070, 'begins': 953, 'lab': 5088, 'crazy': 2150, 'scientist': 7813, 'invented': 4786, 'highly': 4278, 'toxic': 9138, 'poison': 6785, 'kills': 5033, 'victim': 9539, 'makes': 5495, 'died': 2573, 'heart': 4196, 'attack': 725, 'mysterious': 6036, 'criminal': 2181, 'mastermind': 5603, 'breaks': 1233, 'common': 1884, 'criminals': 2182, 'jail': 4857, 'carry': 1484, 'using': 9465, 'then': 8961, 'put': 7107, 'back': 808, 'title': 9064, 'suggests': 8689, 'nearby': 6089, 'girls': 3847, 'provides': 7043, 'victims': 9540, 'monk': 5894, 'dressed': 2817, 'red': 7288, 'around': 628, 'breaking': 1232, 'serious': 7945, 'affair': 303, 'clearly': 1746, 'tongue': 9091, 'cheek': 1621, 'vibe': 9532, 'well': 9747, 'fact': 3299, 'sides': 8113, 'everything': 3162, 'run': 7688, 'big': 1037, 'nicely': 6143, 'throughout': 9017, 'always': 430, 'enough': 3066, 'audience': 749, 'interested': 4748, 'atmosphere': 719, 'superb': 8712, 'colour': 1833, 'scheme': 7800, 'display': 2671, 'edgar': 2929, 'wallace': 9652, 'novel': 6223, 'imagination': 4520, 'locations': 5328, 'killer': 5029, 'lair': 5104, 'host': 4382, 'wild': 9817, 'exotic': 3219, 'animals': 507, 'serve': 7950, 'relevance': 7353, 'help': 4233, 'give': 3849, 'extra': 3279, 'cant': 1424, 'expect': 3221, 'conclusion': 1944, 'fully': 3705, 'after': 320, 'stuff': 8625, 'goes': 3900, 'sort': 8329, 'satisfying': 7769, 'overall': 6446, 'excellent': 3185, 'recommended': 7277, 'pokémon': 6789, 'fan': 3336, 'enjoyed': 3059, 'introduces': 4778, 'legendary': 5195, 'each': 2895, 'adds': 260, 'depth': 2481, 'relationships': 7343, 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'token': 9075, 'grown': 4023, 'captured': 1442, 'essence': 3124, 'imagining': 4525, 'roth': 7651, 'extras': 3281, 'bc': 903, 'thade': 8937, 'chews': 1638, 'amounts': 458, 'lacked': 5094, 'mad': 5458, '1968': 61, 'charlton': 1604, 'heston': 4262, 'taylor': 8864, 'mankind': 5520, 'progressed': 6998, 'unwittingly': 9437, 'sole': 8289, 'salvation': 7736, 'discovers': 2644, 'statue': 8493, 'liberty': 5239, 'species': 8369, 'cerebral': 1556, 'leo': 5209, 'humans': 4422, 'landed': 5116, 'sensual': 7923, 'armor': 624, 'deserved': 2500, 'arrogance': 638, 'ludicrous': 5413, 'landing': 5117, '2001': 101, 'complaining': 1908, 'evolved': 3174, 'overacting': 6445, 'hairy': 4079, 'established': 3128, 'maverick': 5629, 'mute': 6025, 'expectations': 3223, 'currently': 2249, 'ape': 564, 'dominated': 2740, 'charisma': 1598, 'instill': 4704, 'monitor': 5893, 'drawing': 2803, 'throw': 9018, 'shoe': 8063, 'icon': 4470, 'alike': 390, 'irony': 4816, 'apt': 598, 'elevated': 2983, 'chewing': 1637, 'technique': 8880, 'dad': 2273, 'dumb': 2866, 'dumber': 2867, 'beating': 918, 'lesson': 5219, 'demonstrate': 2443, 'muttering': 6027, 'teach': 8867, 'monkeys': 5896, 'firstly': 3490, 'secondly': 7868, 'imbecilic': 4526, 'intend': 4730, 'blowing': 1116, 'confuse': 1961, 'warren': 9686, 'integral': 4722, 'cop': 2068, 'accomplished': 205, 'contained': 2005, 'delivered': 2426, 'constant': 1998, 'discovering': 2643, 'toughness': 9126, 'actresses': 236, 'prisoners': 6958, 'preparing': 6905, 'tolerance': 9079, 'resolve': 7451, 'tested': 8931, 'naked': 6047, 'demands': 2432, 'attributes': 745, 'attitude': 738, 'guts': 4056, 'respond': 7462, 'demme': 2438, 'debut': 2366, 'mentor': 5734, 'roger': 7614, 'desire': 2509, 'stamp': 8453, 'define': 2403, 'current': 2248, 'psychological': 7058, 'states': 8488, 'particular': 6545, 'featuring': 3389, 'warden': 9670, 'de': 2345, 'clockwork': 1768, 'orange': 6386, 'planning': 6742, 'daring': 2312, 'chair': 1564, 'bound': 1191, 'nutty': 6246, 'doc': 2715, 'miller': 5797, 'brown': 1282, 'sassy': 7762, 'sister': 8167, 'environment': 3091, 'fear': 3381, 'cross': 2202, 'wilson': 9828, 'prisoner': 6957, 'sentenced': 7926, 'belle': 980, 'ella': 2989, 'reid': 7330, 'obsession': 6271, 'mcqueen': 5656, 'remove': 7390, 'nude': 6233, 'hugging': 4409, 'arms': 625, 'murdering': 6007, 'relative': 7344, 'dirty': 2622, 'effectively': 2949, 'finale': 3463, 'planned': 6741, 'inflicted': 4641, 'gunfire': 4048, 'impressed': 4558, 'photographic': 6682, 'cinematographer': 1705, 'establish': 3127, 'rooms': 7640, 'task': 8855, 'appropriately': 595, 'crummy': 2218, 'inmates': 4669, 'longing': 5351, 'pits': 6724, 'souls': 8332, 'horrid': 4373, 'madness': 5466, 'repressed': 7425, 'glasses': 3861, 'behaviors': 961, 'contempt': 2010, 'push': 7103, 'handling': 4106, 'uncanny': 9329, 'alliance': 400, 'oppressive': 6379, 'humorous': 4427, 'colorful': 1831, 'personalities': 6648, 'joining': 4923, 'bank': 845, 'robbery': 7586, 'progress': 6997, 'rob': 7582, 'solitary': 8293, 'cat': 1508, 'escapes': 3116, 'horrifying': 4376, 'therapy': 8965, 'session': 7957, 'advantage': 289, 'relates': 7339, 'pretension': 6925, 'hopes': 4365, 'pleased': 6760, 'lee': 5188, 'bang': 844, 'hurt': 4448, 'eyebrows': 3287, 'sale': 7729, 'wondered': 9877, 'macmurray': 5456, 'carole': 1472, 'lombard': 5343, 'table': 8807, 'adaption': 247, 'burlesque': 1332, 'popular': 6815, 'ran': 7180, 'broadway': 1266, '1928': 26, 'stanwyck': 8464, 'originated': 6407, 'starred': 8473, 'nancy': 6055, 'carroll': 1482, 'talkies': 8834, 'betty': 1025, 'grable': 3949, 'dan': 2290, 'smiles': 8250, 'album': 372, 'al': 365, 'ruby': 7672, 'singer': 8155, 'jazz': 4877, 'trumpeter': 9263, 'latin': 5141, 'anthony': 535, 'quinn': 7135, 'swing': 8786, 'century': 1555, 'jason': 4873, 'freddy': 3662, 'workout': 9899, 'unseen': 9417, 'deserves': 2502, 'explanation': 3243, 'clarify': 1725, 'acquired': 222, 'oddly': 6296, 'classes': 1731, 'earnest': 2905, 'capable': 1429, 'stopping': 8552, 'factor': 3300, 'dies': 2575, 'sessions': 7958, 'explosive': 3262, 'beds': 936, 'hundreds': 4431, 'exposed': 3264, 'measure': 5670, 'uncomfortable': 9331, 'creepy': 2173, 'creative': 2159, 'creativity': 2160, 'ignore': 4496, 'premise': 6901, 'unusual': 9431, 'ghost': 3815, 'medium': 5687, 'narration': 6058, 'path': 6571, 'peaks': 6604, 'charges': 1597, 'escaping': 3117, 'kidnaps': 5025, 'downward': 2781, 'aspects': 669, 'strongest': 8603, 'aspect': 668, 'aside': 662, 'amount': 457, 'convinced': 2058, 'ruthless': 7702, 'bold': 1143, 'punches': 7079, 'anal': 470, 'boundaries': 1192, 'ignored': 4497, 'gladly': 3854, 'achieved': 215, 'noticeable': 6215, 'grade': 3955, 'equipment': 3101, 'choices': 1664, 'cemetery': 1544, 'issue': 4836, 'grave': 3980, 'imply': 4549, 'loosely': 5361, 'firm': 3487, 'dishonest': 2663, 'kidnap': 5023, 'torture': 9113, 'likewise': 5269, 'ma': 5445, 'overly': 6457, 'cruel': 2213, 'sadistic': 7714, 'marginally': 5545, 'neighbor': 6109, 'offering': 6314, 'fool': 3577, 'claims': 1722, 'vast': 9500, 'majority': 5491, 'nap': 6057, 'netflix': 6126, 'warned': 9679, 'knowing': 5064, 'campy': 1407, 'exception': 3189, 'kevin': 5012, 'ritter': 7568, 'halfway': 4083, 'riley': 7546, 'exceptionally': 3191, 'shocked': 8058, 'ultra': 9317, 'fantasies': 3343, 'technological': 8883, 'nobody': 6172, 'cares': 1457, 'mocking': 5869, 'core': 2077, 'edgy': 2933, 'random': 7182, 'grainy': 3962, 'boxers': 1200, 'faces': 3296, 'digs': 2592, 'cultists': 2236, 'overtones': 6460, 'writes': 9934, 'produces': 6977, 'coffee': 1803, 'element': 2979, 'keeping': 4997, 'cinematography': 1706, 'witnessed': 9865, 'plan': 6737, 'witness': 9864, 'stiles': 8533, 'unsuccessful': 9421, 'trite': 9240, 'forgettable': 3601, 'entirely': 3086, 'wiped': 9846, 'records': 7281, 'realized': 7248, 'likely': 5267, 'anybody': 551, 'collection': 1820, 'rid': 7531, 'hand': 4100, 'mud': 5989, 'window': 9833, 'deed': 2389, 'sgt': 7984, 'dylan': 2891, 'mcdermott': 5646, 'practice': 6869, 'dealer': 2351, 'conflict': 1955, 'conscience': 1980, 'freeman': 3666, 'spacey': 8350, 'promise': 7008, 'justin': 4975, 'timberlake': 9045, 'pollack': 6799, 'opportunity': 6373, 'repeatedly': 7405, 'choose': 1666, 'craft': 2135, 'sells': 7904, 'millions': 5800, 'automatically': 772, 'translate': 9173, 'successfully': 8667, 'hardcore': 4133, 'sync': 8803, 'sudden': 8674, 'sniper': 8263, 'operation': 6367, 'machinery': 5451, 'thoroughly': 8993, 'alfred': 381, 'hitchcock': 4309, 'revolves': 7512, 'pompous': 6801, 'jumps': 4964, 'sees': 7894, 'stranded': 8566, 'rescued': 7437, 'fishing': 3495, 'boat': 1130, 'joan': 4910, 'barry': 866, 'unfaithful': 9365, 'sly': 8239, 'grew': 4002, 'ustinov': 9466, 'wanders': 9660, 'breath': 1236, 'inconsequential': 4596, 'embezzler': 3003, 'posing': 6835, 'secretary': 7871, 'fired': 3483, 'deadpan': 2348, 'karl': 4984, 'malden': 5500, 'sleazy': 8208, 'coup': 2114, 'dazzling': 2342, 'seat': 7862, 'rating': 7211, 'politics': 6798, 'nerve': 6121, 'ride': 7533, 'product': 6979, 'hip': 4294, 'hop': 4358, 'electronic': 2975, 'generation': 3780, 'authentic': 764, 'strings': 8593, 'culture': 2238, 'dj': 2713, 'cheesy': 1625, 'competition': 1905, 'steady': 8500, 'nyc': 6248, 'essential': 3125, 'athletic': 717, 'stylistic': 8641, 'seasoned': 7860, 'nation': 6071, 'journalist': 4934, 'forward': 3622, 'critical': 2190, 'britain': 1262, 'ealing': 2898, 'comedies': 1853, 'victory': 9544, '1945': 40, 'hearts': 4202, 'satire': 7765, 'upper': 9448, 'mob': 5864, 'contain': 2004, 'political': 6794, 'applied': 586, 'pimlico': 6713, 'district': 2693, 'mile': 5791, 'victoria': 9542, 'independent': 4610, 'area': 609, 'iv': 4847, 'wishes': 9853, 'inhabitants': 4658, 'royal': 7667, 'laws': 5160, 'sell': 7901, 'whomever': 9801, 'goods': 3924, 'authorities': 767, 'horrified': 4375, 'suit': 8691, 'larger': 5130, 'bureaucracy': 1327, 'imposed': 4553, 'accepted': 196, 'growing': 4022, 'reviewer': 7503, 'stated': 8485, 'targets': 8852, 'targeted': 8851, 'san': 7743, '1949': 43, 'keen': 4995, 'stress': 8583, 'patriotism': 6581, 'sticking': 8530, 'contrast': 2028, 'presented': 6910, 'uk': 9314, 'drops': 2836, 'pour': 6858, 'global': 3871, 'warming': 9676, 'slightly': 8224, 'belief': 971, 'contrary': 2027, 'wet': 9765, 'stanley': 8463, 'arthur': 644, 'politician': 6796, 'cameo': 1396, 'margaret': 5542, 'pulling': 7072, 'ensemble': 3068, 'contribution': 2032, 'recent': 7267, 'favourite': 3377, 'hilarity': 4283, 'struggles': 8609, 'recreate': 7285, 'neatly': 6092, 'exploit': 3250, 'shamelessly': 8008, 'males': 5502, 'kick': 5017, 'honestly': 4347, 'wishing': 9854, 'demise': 2437, 'spare': 8354, 'uwe': 9473, 'boll': 1144, 'challenge': 1565, 'produce': 6973, 'arguably': 612, 'section': 7874, 'zombies': 9996, 'cap': 1427, 'zombie': 9995, 'meaning': 5663, 'harmless': 4140, 'blood': 1109, 'closet': 1777, 'bursts': 1341, 'bin': 1054, 'milk': 5794, 'decaying': 2370, 'according': 207, 'received': 7264, 'cinemas': 1703, 'separate': 7933, 'rolled': 7619, 'mentions': 5733, 'abruptly': 176, 'replaced': 7411, 'inane': 4572, 'cleaning': 1744, 'apartment': 561, 'wong': 9883, 'wai': 9634, 'hidden': 4267, 'acted': 225, 'brighter': 1254, 'angelina': 493, 'jolie': 4928, 'sweet': 8780, 'changes': 1579, 'optimistic': 6381, 'curly': 2247, 'sue': 8676, 'touched': 9122, 'los': 5366, 'south': 8342, 'confident': 1952, 'streetwise': 8580, 'elder': 2971, '17th': 15, 'birthday': 1063, 'manipulative': 5519, 'mistress': 5854, 'unfolds': 9367, 'overt': 6459, 'pacing': 6476, 'explicit': 3245, 'points': 6784, 'memento': 5714, 'pulp': 7075, 'evolve': 3173, 'chile': 1650, 'countries': 2109, 'skits': 8196, 'joke': 4926, 'fest': 3413, 'groove': 4011, 'proper': 7019, 'uber': 9310, 'olympics': 6343, 'clown': 1784, 'ninety': 6162, 'dung': 2873, 'model': 5872, 'kentucky': 5009, 'fried': 3676, 'skit': 8195, 'lifetime': 5250, 'credibility': 2165, 'lara': 5127, 'patti': 6584, 'blink': 1101, 'threatening': 9004, 'dares': 2310, 'behave': 956, 'trusted': 9266, 'medicine': 5682, 'stairs': 8447, 'scale': 7784, '95': 154, 'batch': 887, 'popcorn': 6810, 'apple': 585, 'respectable': 7457, 'nevertheless': 6131, 'embarrassed': 2999, 'depressed': 2478, 'goodness': 3923, 'twists': 9300, 'james': 4861, 'belushi': 989, 'hood': 4351, 'stolen': 8543, '12': 8, 'gangsters': 3745, 'sheriff': 8039, 'timothy': 9054, 'dalton': 2282, 'wont': 9884, 'jump': 4961, 'board': 1125, 'minute': 5820, 'trip': 9234, 'eating': 2921, 'sensitive': 7921, 'bulimia': 1314, 'causes': 1525, 'alison': 392, 'lohman': 5339, 'spectacular': 8373, 'schools': 7807, 'convey': 2048, 'anguish': 503, 'pressure': 6917, 'degree': 2411, 'accuracy': 210, 'precise': 6881, 'measured': 5671, 'trauma': 9188, 'rising': 7561, 'hysteria': 4463, 'desperation': 2516, 'reaches': 7227, 'unbearable': 9324, 'intensity': 4735, 'immense': 4535, 'finely': 3472, 'achievement': 216, 'shea': 8027, 'proud': 7036, 'despair': 2513, 'sympathise': 8800, 'depths': 2482, 'sympathetic': 8799, 'motives': 5962, 'fresh': 3671, 'hackneyed': 4066, 'hokey': 4321, 'strikes': 8590, 'pseudo': 7051, 'enlightenment': 3063, 'religion': 7359, 'hide': 4268, 'oz': 6471, 'precious': 6880, 'resources': 7455, 'water': 9706, 'shut': 8103, 'photographer': 6681, 'roommate': 7639, 'cartoon': 1489, 'cousin': 2123, 'sensibilities': 7918, 'perspective': 6652, 'sixty': 8179, 'hyper': 4459, 'faded': 3306, 'lighten': 5255, 'float': 3539, 'caricatures': 1462, 'celebrities': 1538, 'cartoons': 1491, '1930s': 29, '1940s': 36, 'terribly': 8919, 'crosby': 2201, 'hated': 4158, 'occasion': 6279, 'sigh': 8116, 'drab': 2786, 'suspenseful': 8765, 'despicable': 2517, 'bernsen': 1008, 'benefits': 995, 'performers': 6634, 'rated': 7208, 'gene': 3775, 'behaves': 958, 'el': 2969, 'yesterday': 9966, 'sickness': 8108, 'sexuality': 7979, 'rage': 7156, 'filled': 3449, 'suffer': 8677, 'clean': 1742, 'blues': 1120, '1944': 39, 'jam': 4860, 'marie': 5548, 'sunny': 8708, 'bring': 1258, 'exposure': 3267, 'musicians': 6018, 'angles': 499, '40s': 131, 'notes': 6212, 'filmed': 3454, 'reflection': 7310, 'youtube': 9983, 'skin': 8190, 'scariest': 7791, 'myers': 6029, 'boogeyman': 1159, 'terrifying': 8922, 'effect': 2947, 'loomis': 5358, 'describes': 2494, 'devil': 2548, 'jamie': 4862, 'partying': 6553, 'virgin': 9580, 'pays': 6596, 'janet': 4865, 'leigh': 5199, 'lock': 5330, 'doors': 2757, 'windows': 9834, 'indie': 4620, 'blow': 1115, 'alot': 414, 'theaters': 8948, 'vhs': 9530, '1992': 88, 'reflect': 7307, 'values': 9485, 'schemes': 7801, 'debt': 2365, 'economic': 2924, 'exploits': 3254, 'forcing': 3592, 'cards': 1449, 'raises': 7169, 'saving': 7777, 'streisand': 8581, 'familiar': 3332, 'performer': 6633, 'celine': 1540, 'vibrancy': 9533, 'energy': 3047, 'enthusiasm': 3083, 'vulnerability': 9629, 'performs': 6636, 'park': 6532, 'concert': 1940, 'spontaneous': 8412, 'rehearsed': 7329, 'wall': 9651, 'ticket': 9033, 'vocals': 9608, 'judy': 4953, 'rodgers': 7610, 'harold': 4141, '1970s': 64, 'albums': 373, 'shrieking': 8101, 'struggle': 8607, 'improve': 4564, 'singers': 8156, 'melodies': 5703, 'undoubtedly': 9357, 'blows': 1118, 'crawford': 2148, 'cd': 1531, 'reminding': 7385, 'insist': 4685, 'duets': 2861, 'advised': 298, 'highway': 4279, 'cbs': 1530, 'guests': 4040, 'treat': 9199, 'phenomenon': 6667, 'amazed': 435, 'difference': 2578, '01': 2, '1st': 97, 'barbra': 854, 'orchestra': 6389, 'bored': 1171, 'shorter': 8079, 'rendition': 7394, 'auto': 770, 'pilot': 6711, '2nd': 120, 'depression': 2480, 'amidst': 449, 'goodman': 3922, 'historic': 4303, 'dislike': 2665, 'tears': 8875, 'sun': 8705, 'medley': 5688, 'explaining': 3241, 'fanny': 3341, 'sang': 7748, '1922': 25, 'dress': 2816, 'gown': 3945, 'urgent': 9455, 'charged': 1596, 'glimpse': 3868, 'understated': 9349, 'boxing': 1202, 'prevents': 6933, 'calling': 1386, 'robert': 7589, 'wise': 9849, 'newman': 6135, 'likes': 5268, 'corbett': 2076, 'sport': 8417, 'crucial': 2211, 'transition': 9172, 'bare': 856, 'gloved': 3880, 'illegal': 4504, 'spectacle': 8372, 'acceptance': 195, 'delightfully': 2422, 'alexis': 380, 'win': 9830, 'match': 5610, 'sullivan': 8697, 'romanticism': 7627, 'sports': 8418, 'move': 5972, 'raging': 7158, 'bull': 1316, 'expressed': 3269, 'emotion': 3013, 'steam': 8504, 'annual': 527, 'rounds': 7659, 'seats': 7863, 'farting': 3355, 'filler': 3450, 'wizard': 9869, 'insists': 4688, 'critique': 2196, 'defeats': 2397, 'quarter': 7119, 'rogers': 7615, 'surprises': 8744, 'provided': 7042, 'imaginations': 4521, 'originally': 6405, 'propaganda': 7018, 'fathers': 3370, 'experienced': 3230, 'imitation': 4530, 'copious': 2072, 'pain': 6489, 'bloodless': 1111, 'shattering': 8024, 'ho': 4316, 'assigned': 683, 'hopper': 4368, 'investigate': 4792, 'pains': 6492, 'prevented': 6931, 'squandered': 8433, 'horse': 4379, 'dickens': 2567, 'bath': 889, 'convoluted': 2062, 'improbable': 4563, 'reactions': 7231, 'exist': 3211, 'dry': 2848, 'productive': 6982, 'investment': 4796, '2003': 103, 'expectation': 3222, 'perverse': 6655, 'japan': 4870, 'unnatural': 9396, 'kinky': 5042, 'fathom': 3371, 'sights': 8119, 'notably': 6208, 'fare': 3349, 'designs': 2508, 'gruesome': 4027, 'balance': 830, 'unlikely': 9395, 'prestigious': 6918, 'catch': 1511, 'trained': 9160, 'grasp': 3975, 'execution': 3207, 'tradition': 9149, 'carmen': 1469, 'spears': 8365, 'wannabe': 9663, 'ears': 2907, 'supreme': 8733, 'teachers': 8869, 'standing': 8459, 'teacher': 8868, 'induced': 4625, 'taped': 8845, 'pregnancy': 6894, 'affects': 309, 'demonstrated': 2444, 'childish': 1646, 'properly': 7020, 'educated': 2942, 'whiny': 9790, 'fruit': 3693, 'wore': 9892, 'eight': 2962, 'edition': 2940, 'riot': 7552, 'oblivious': 6258, 'spy': 8430, 'dining': 2604, 'dewey': 2554, 'rip': 7553, 'penn': 6617, 'chances': 1574, 'seasons': 7861, 'unfortunate': 9369, 'depicting': 2472, 'bravo': 1226, 'cooper': 2067, 'winter': 9844, 'capsule': 1437, 'roaring': 7580, 'imagined': 4524, 'mountain': 5965, 'brutally': 1289, 'disappear': 2625, 'believed': 975, 'signed': 8123, 'certificate': 1559, 'authenticity': 765, 'offered': 6313, 'iranian': 4808, 'appreciated': 588, 'anthropologist': 536, 'sufficient': 8682, 'stock': 8541, 'recorded': 7279, 'fancy': 3338, 'resulting': 7475, 'multiple': 5996, 'inter': 4742, 'titles': 9066, 'spin': 8392, 'peoples': 6620, 'duty': 2882, 'desert': 2497, 'ball': 832, 'chang': 1576, 'commercial': 1876, 'kong': 5070, '1933': 30, 'wind': 9832, '1976': 70, '1999': 95, 'lumet': 5422, 'ground': 4015, 'flops': 3545, 'held': 4220, 'till': 9042, 'financial': 3466, 'suburban': 8659, 'jewelry': 4902, 'owned': 6467, 'elderly': 2972, 'concerned': 1937, 'aftermath': 321, 'differing': 2582, 'older': 6332, 'carrying': 1485, 'vice': 9535, 'versa': 9520, 'hardly': 4135, 'accounts': 209, 'heroin': 4254, 'scheming': 7802, 'seymour': 7982, 'supported': 8727, 'ethan': 3139, 'hawke': 4170, 'bullied': 1319, 'finney': 3480, 'marisa': 5555, 'tomei': 9085, 'cheating': 1618, 'puts': 7108, 'literally': 5301, 'comfort': 1856, 'origins': 6408, 'kelly': 5003, 'untrue': 9430, 'turkeys': 9284, 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'hooper': 4355, 'pity': 6726, 'grind': 4006, 'unremarkable': 9411, 'stinker': 8539, 'considerable': 1986, 'cold': 1813, 'smuggling': 8256, 'tricked': 9223, 'exaggerated': 3179, 'memory': 5720, 'elm': 2991, 'exists': 3216, 'differently': 2581, 'bush': 1347, 'passed': 6559, 'learn': 5177, 'realm': 7252, 'beside': 1010, 'springwood': 8429, 'performed': 6632, 'goo': 3918, 'masterpiece': 5604, 'underrated': 9343, 'misunderstood': 5856, 'tastes': 8858, 'tool': 9097, 'blew': 1098, 'niche': 6144, 'alleged': 396, 'loaded': 5319, 'bear': 910, 'author': 766, 'nazi': 6085, 'irish': 4812, 'personally': 6650, 'vital': 9599, 'extremes': 3285, 'reverse': 7499, 'gear': 3767, 'headed': 4180, 'erotic': 3109, 'mistakes': 5851, 'starters': 8478, 'hobgoblins': 4318, 'closely': 1773, 'bargain': 859, 'basement': 874, 'embarrassing': 3000, 'inappropriate': 4573, 'fx': 3723, 'meddling': 5678, 'track': 9142, 'scripts': 7846, 'rick': 7530, 'sloane': 8231, 'separation': 7935, 'church': 1696, 'underwear': 9354, 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'cannibalism': 1420, 'irrational': 4817, 'explained': 3240, 'unfair': 9364, 'significantly': 8126, 'demented': 2435, 'infuriating': 4652, 'underdog': 9339, 'productions': 6981, 'romero': 7630, 'hollow': 4330, 'occurred': 6286, 'emotionally': 3015, 'standout': 8460, 'fades': 3307, 'slightest': 8223, 'arty': 654, 'pursue': 7097, 'mclaglen': 5653, 'tour': 9128, 'dublin': 2853, 'evoked': 3170, 'techniques': 8881, 'noirs': 6176, 'detail': 2528, 'frankie': 3653, 'ford': 3593, 'praying': 6874, 'gaelic': 3728, 'steiner': 8509, '1939': 34, '1935': 32, 'miserable': 5833, 'committed': 1880, 'knife': 5054, 'calm': 1388, 'smiling': 8251, 'throat': 9014, 'agent': 331, 'bend': 992, 'continuity': 2023, 'eager': 2897, 'groom': 4010, 'bride': 1245, 'bathroom': 891, 'entering': 3074, 'reception': 7269, 'cecil': 1532, 'demille': 2436, 'epic': 3094, 'finest': 3475, 'hysterical': 4464, 'amoral': 455, 'calamity': 1380, 'occasional': 6280, 'pastiche': 6567, 'lore': 5364, 'jesse': 4896, 'abraham': 174, 'subtlety': 8657, 'masses': 5596, 'frontal': 3689, 'industrial': 4628, 'washington': 9695, 'composed': 1918, 'autobiography': 771, 'adopted': 276, 'subsequent': 8651, 'westerns': 9764, 'whereby': 9779, 'countless': 2108, 'thousand': 8999, 'skies': 8186, 'varied': 9495, 'hayes': 4174, 'crowd': 2206, 'thhe': 8974, 'mutant': 6023, 'jonathan': 4930, 'entertain': 3077, 'birth': 1062, 'prepare': 6903, 'hint': 4291, 'scientists': 7814, 'briefly': 1251, 'rejects': 7336, 'labor': 5090, 'idiotic': 4488, 'mutants': 6024, 'marines': 5552, 'aliens': 389, 'exact': 3177, 'opposite': 6376, 'hills': 4287, 'attachment': 724, 'brief': 1250, 'inferior': 4640, 'cake': 1379, 'sloth': 8233, 'helps': 4238, 'ruth': 7701, 'ice': 4468, 'cream': 2151, 'visceral': 9587, 'toned': 9090, 'stood': 8548, 'strike': 8589, 'crisis': 2186, 'fighter': 3441, 'alas': 368, 'lowest': 5395, 'scores': 7819, 'dreadful': 2808, 'uninspired': 9377, 'bother': 1182, 'cash': 1497, 'lt': 5400, 'buddy': 1299, 'screw': 7839, 'treated': 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'teenager': 8891, 'photograph': 6679, 'accepts': 198, 'loses': 5370, 'christina': 1686, 'patty': 6586, 'hearst': 4195, 'walken': 9647, 'transformed': 9171, 'connery': 1973, 'shy': 8104, 'pretend': 6922, 'democratic': 2439, 'forgot': 3606, 'bitter': 1070, 'criticism': 2192, 'capitalism': 1434, 'nuclear': 6232, 'powered': 6862, 'below': 987, 'thick': 8975, 'attacked': 726, 'electric': 2974, 'communicate': 1885, 'dear': 2358, 'bugs': 1307, 'containing': 2006, 'pointing': 6782, 'fingers': 3477, 'laughter': 5150, 'bo': 1123, 'derek': 2486, 'revolutionary': 7510, 'worthwhile': 9914, 'widowed': 9812, 'experiencing': 3232, 'transformation': 9170, 'fitting': 3500, 'tony': 9094, 'pleasant': 6757, 'bruce': 1284, 'riveting': 7573, 'scripted': 7844, 'rapist': 7201, 'russo': 7699, 'inform': 4646, 'realizes': 7249, 'wallet': 9653, 'pat': 6568, 'terry': 8927, 'diana': 2563, 'degrades': 2410, 'rape': 7197, 'opponents': 6371, 'displays': 2674, 'nemesis': 6117, 'creditable': 2168, 'creep': 2172, 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4710, 'lucas': 5402, 'secondary': 7867, 'education': 2943, 'teaching': 8870, 'sarcastic': 7759, 'judging': 4949, 'benny': 999, 'gibson': 3823, 'publicity': 7066, 'studios': 8622, 'sony': 8319, 'downhill': 2775, 'inexplicably': 4636, 'newsreel': 6140, 'tokyo': 9076, 'poorest': 6807, 'imaginary': 4519, 'slum': 8238, 'preferred': 6892, 'infants': 4638, 'rewind': 7517, 'carol': 1471, 'parks': 6535, 'downloaded': 2776, 'kings': 5040, 'demon': 2440, 'everytown': 3163, 'represents': 7424, '1966': 59, 'futuristic': 3721, 'civilization': 1717, 'wings': 9838, 'dedicated': 2386, 'reminiscent': 7387, 'metropolis': 5767, 'architecture': 605, '1969': 62, 'inherent': 4660, 'swept': 8782, 'azaria': 800, 'arkin': 619, 'dire': 2610, 'stereo': 8518, 'typed': 9305, 'zeta': 9991, 'minus': 5819, 'originality': 6404, 'mexican': 5768, 'elaborate': 2970, 'lowering': 5394, 'tender': 8907, '6th': 143, 'wilcox': 9816, 'underdeveloped': 9338, 'pushing': 7106, 'kristin': 5079, 'diminishes': 2601, 'rerun': 7435, 'garden': 3750, 'pbs': 6598, 'breakfast': 1231, 'tiffany': 9039, 'barrymore': 867, 'leslie': 5216, 'holly': 4331, 'nathan': 6070, 'gooding': 3921, 'fallon': 3327, 'bombs': 1148, 'selection': 7898, 'hesitant': 4260, 'reel': 7299, '1977': 71, 'shoulder': 8086, 'severed': 7973, 'waterfall': 9707, 'facing': 3298, 'startled': 8480, 'resembled': 7444, 'slater': 8205, 'sinks': 8162, 'intent': 4736, 'hopkins': 4367, 'slipstream': 8230, 'ambiguous': 441, 'experiment': 3233, 'hurled': 4444, 'rudimentary': 7675, 'shaky': 8001, 'reflecting': 7309, 'rocking': 7603, 'drawings': 2804, 'painted': 6494, 'letter': 5227, 'hurry': 4447, 'heir': 4217, 'interviews': 4767, 'yacht': 9950, 'bathing': 890, 'execute': 3205, 'orlando': 6409, 'africa': 318, 'miniseries': 5815, 'taboo': 8809, 'apocalyptic': 567, 'tail': 8816, 'blatantly': 1088, 'vader': 9475, 'frodo': 3684, 'hello': 4228, 'zodiac': 9993, 'nonetheless': 6186, 'basketball': 883, 'providing': 7044, 'profanity': 6984, 'rosie': 7649, 'cleveland': 1749, 'crippled': 2185, 'safe': 7717, 'jeter': 4901, 'toto': 9120, 'gosha': 3936, 'sakamoto': 7726, 'takechi': 8820, 'term': 8915, 'shogunate': 8065, 'orders': 6395, 'loyalist': 5398, 'emperor': 3019, 'clan': 1724, 'revealing': 7495, 'significance': 8124, 'closest': 1776, 'traitor': 9162, 'sway': 8774, 'potentially': 6854, 'feudal': 3418, 'relations': 7341, 'instruments': 4713, 'samurai': 7742, 'inevitably': 4633, 'interests': 4751, 'arrived': 636, 'ships': 8053, 'elite': 2987, 'inclined': 4583, 'obtain': 6275, 'represented': 7423, 'yarn': 9956, 'plodding': 6765, 'rejected': 7334, 'bonanza': 1150, 'cancellation': 1413, 'dexter': 2555, 'offs': 6322, 'misadventures': 5830, 'replacement': 7412, 'fiery': 3435, 'sisters': 8168, 'consist': 1991, 'twins': 9297, 'geniuses': 3787, 'swoon': 8790, 'guinea': 4045, 'services': 7955, 'clone': 1769, 'unlikeable': 9394, 'ripped': 7556, 'arnold': 627, 'schwarzenegger': 7809, 'ranks': 7193, 'threw': 9007, 'clinic': 1762, 'conan': 1926, 'manic': 5516, 'darryl': 2323, 'contestants': 2014, 'privileged': 6960, 'ribs': 7523, 'redeemed': 7290, 'hysterically': 4465, 'capturing': 1444, 'wrapped': 9922, 'behaved': 957, 'absorbing': 182, 'mastroianni': 5608, 'string': 8592, 'trodden': 9246, 'lethal': 5224, 'assets': 682, 'caroline': 1473, 'rex': 7519, 'salman': 7734, 'rani': 7190, 'preity': 6896, 'raj': 7171, 'priya': 6961, 'madhubala': 5461, 'agrees': 340, 'chori': 1676, 'chupke': 1695, 'ne': 6087, 'hai': 4073, 'mann': 5521, 'mehndi': 5697, 'laying': 5165, 'sentiment': 7928, 'countryside': 2111, 'wretched': 9929, 'construction': 2002, 'homo': 4344, 'refreshing': 7313, 'jumping': 4963, 'banality': 838, 'baseball': 872, 'obsessive': 6272, 'adapted': 246, 'sox': 8345, 'tickets': 9034, 'fanatic': 3337, 'misses': 5843, 'attend': 734, 'museum': 6013, 'verge': 9517, '2004': 104, 'joyous': 4940, 'seventies': 7969, 'superlative': 8717, 'shadow': 7988, 'boxes': 1201, 'indifferent': 4621, 'studied': 8619, 'sinking': 8161, 'virile': 9582, 'breathe': 1237, 'housewife': 4394, 'lightweight': 5262, 'omen': 6346, 'nest': 6125, 'charismatic': 1599, 'neighbors': 6111, 'moronic': 5941, 'painting': 6495, 'harrington': 4144, 'maid': 5480, 'evoke': 3169, 'pack': 6478, 'salesman': 7732, 'assault': 676, 'duke': 2863, 'advocate': 300, 'afflicted': 313, 'bipolar': 1059, 'labeled': 5089, 'psychiatric': 7054, 'household': 4392, 'ross': 7650, '1950': 44, 'marries': 5571, 'divorces': 2711, 'medication': 5681, 'magazine': 5471, 'ignorance': 4494, 'generic': 3782, 'african': 319, 'vibrant': 9534, 'astro': 708, 'dub': 2850, 'gus': 4053, 'lola': 5342, 'resemblances': 7442, 'ninja': 6163, 'riders': 7534, 'racial': 7148, 'gender': 3773, 'sasquatch': 7761, 'invited': 4800, 'pleasantly': 6758, 'lifeless': 5248, 'interpreted': 4763, 'proceeds': 6970, 'greta': 4001, 'spinal': 8393, 'syndrome': 8804, 'neglects': 6107, 'georges': 3797, 'highlights': 4277, 'reinforces': 7332, 'neglect': 6105, 'copied': 2070, 'trashy': 9187, 'bursting': 1340, 'houses': 4393, 'instructed': 4708, 'comforting': 1859, 'retains': 7479, 'burdened': 1326, 'tossed': 9117, 'tediously': 8888, 'humane': 4419, 'aussie': 760, 'greener': 3996, 'shouts': 8089, 'endings': 3038, 'cleese': 1747, 'draft': 2788, 'hoot': 4356, 'betrays': 1020, 'paths': 6575, 'knowingly': 5065, 'egg': 2955, 'dynamics': 2893, 'bands': 842, 'behr': 965, 'livien': 5312, 'confess': 1949, 'beatles': 919, 'tia': 9029, 'maria': 5547, 'reached': 7226, 'monaghan': 5888, 'acknowledge': 220, 'complexity': 1915, 'insisted': 4686, 'invading': 4783, 'inspector': 4690, 'dominant': 2738, 'shake': 7995, 'informer': 4650, 'interpret': 4760, 'controlled': 2035, 'passive': 6565, 'predictably': 6889, 'drugged': 2841, 'depends': 2469, 'precision': 6883, 'focusing': 3560, 'coldly': 1814, 'observe': 6265, 'sentimentality': 7930, 'eventual': 3154, 'concluding': 1943, 'locale': 5323, 'admits': 271, 'ambiguity': 440, 'survivors': 8758, 'symbolic': 8797, 'presidential': 6914, 'sincere': 8152, 'limit': 5272, 'perceived': 6622, '1894': 18, 'lumiere': 5423, 'factory': 3302, 'manufactured': 5530, 'enterprise': 3075, '200': 99, 'edison': 2935, 'celluloid': 1543, 'lens': 5207, 'fps': 3635, 'inventing': 4787, 'cranked': 2140, 'projector': 7004, 'riding': 7539, 'cavalry': 1528, 'des': 2490, 'projected': 7002, 'communities': 1888, 'entrance': 3089, 'exterior': 3277, 'gates': 3759, 'photographs': 6683, 'crank': 2139, 'wonderland': 9881, 'vile': 9566, 'emerge': 3005, 'merge': 5743, 'amid': 448, 'emoting': 3012, 'naturalistic': 6077, 'wicked': 9806, 'kilmer': 5034, 'relentlessly': 7352, 'inches': 4578, 'hangs': 4113, 'strutting': 8613, 'begging': 949, 'pivotal': 6727, 'awaiting': 783, 'catholic': 1518, 'elsewhere': 2994, 'bestiality': 1013, 'casts': 1505, 'glance': 3858, 'deeds': 2390, 'hesitation': 4261, 'troubled': 9254, 'strictly': 8588, 'lex': 5235, 'walt': 9656, 'ally': 407, 'exchange': 3196, 'retrieve': 7485, 'tip': 9059, 'ugh': 9311, 'headstrong': 4185, 'damned': 2288, 'profit': 6990, 'reluctant': 7362, 'muppets': 6002, 'geared': 3768, 'frog': 3685, 'mouth': 5969, 'trailers': 9158, 'crown': 2209, 'sophomore': 8326, 'interface': 4752, 'morals': 5929, 'pushed': 7104, 'marching': 5539, 'observer': 6267, 'transparent': 9177, 'confession': 1950, 'stark': 8471, 'affirmative': 311, 'raised': 7168, 'coincidentally': 1809, 'empathetic': 3017, 'occurrence': 6287, 'citizens': 1714, 'vehicles': 9509, 'proof': 7016, 'brains': 1216, 'springer': 8426, 'undeniably': 9336, 'ringmaster': 7549, 'requisite': 7434, 'triangle': 9217, 'rusty': 7700, 'hapless': 4120, 'culminating': 2232, 'altman': 427, 'habit': 4064, 'squalor': 8432, 'errors': 3113, 'screws': 7842, 'simplest': 8143, 'harder': 4134, 'nickelodeon': 6148, 'severely': 7974, 'damaged': 2284, 'exhibit': 3210, 'bergman': 1003, 'tarzan': 8853, 'weissmuller': 9744, 'weismuller': 9743, 'rugged': 7676, 'denny': 2453, 'maureen': 5628, 'kisses': 5047, 'unthinkable': 9426, 'virginia': 9581, 'huston': 4454, 'sparkling': 8360, 'mexicans': 5769, 'fierce': 3434, 'harris': 4145, 'enemies': 3044, 'uneven': 9360, 'testing': 8932, 'stronger': 8602, 'hugs': 4414, 'mysteriously': 6037, 'paquin': 6518, 'unnecessarily': 9397, 'relies': 7358, 'tolkien': 9080, 'recognizable': 7272, 'bakshi': 829, 'decline': 2382, 'burden': 1325, 'increases': 4604, 'liberties': 5238, 'explores': 3258, 'liking': 5270, 'chillingly': 1654, 'dangerously': 2301, 'documented': 2722, 'prototype': 7034, 'equal': 3098, 'alternative': 425, 'zoo': 9999, 'ignoring': 4499, 'northern': 6201, 'surfing': 8739, 'fisherman': 3494, 'placid': 6733, 'surf': 8737, 'injuries': 4667, 'everywhere': 3164, 'carrere': 1477, 'mcnamara': 5654, 'online': 6355, 'root': 7642, 'kudos': 5083, 'networks': 6128, 'vices': 9536, 'stability': 8441, 'gillian': 3834, 'mannerisms': 5525, 'gestures': 3808, 'contrasting': 2029, 'elementary': 2980, 'competent': 1904, 'leering': 5189, 'travelogue': 9193, 'strut': 8612, 'dani': 2303, 'madly': 5464, 'enters': 3076, 'warfield': 9672, 'jealousy': 4879, 'hunted': 4439, 'hunters': 4441, 'murray': 6011, 'prey': 6938, 'korean': 5074, 'peaked': 6603, 'succeeded': 8662, 'blockbusters': 1105, 'mainland': 5483, 'digitally': 2590, 'legends': 5196, 'lol': 5341, 'cousins': 2124, 'memories': 5719, 'discount': 2639, 'bennett': 998, 'theatres': 8950, '1985': 80, 'attenborough': 733, 'spark': 8356, 'lift': 5251, 'uneasy': 9358, 'regime': 7322, 'proverbial': 7039, 'parking': 6534, 'tasty': 8859, 'laden': 5099, 'ruining': 7679, 'dinosaurs': 2608, 'bite': 1067, 'terrorists': 8926, 'hi': 4265, 'rubber': 7669, 'rips': 7558, 'marine': 5551, 'elephant': 2982, 'roars': 7581, 'sized': 8181, 'drift': 2821, 'edit': 2936, 'indicate': 4616, 'superbly': 8713, '1954': 49, 'bud': 1297, 'daddy': 2274, 'facial': 3297, 'corey': 2078, 'jet': 4900, 'yuk': 9985, 'bitchy': 1066, 'artwork': 653, 'butch': 1355, 'mammy': 5506, 'lazy': 5166, 'slams': 8200, 'snatch': 8260, 'ray': 7220, 'symbolism': 8798, 'ritchie': 7567, 'mister': 5852, 'fellows': 3403, 'mainstream': 5485, 'outline': 6434, 'columbine': 1837, 'massacre': 5595, 'inspirational': 4692, 'athena': 716, 'gadget': 3727, 'chan': 1572, 'miracles': 5825, 'vary': 9498, 'lin': 5276, 'cheung': 1635, 'shootout': 8070, 'woo': 9885, 'transport': 9178, 'chans': 1583, 'storey': 8556, 'factors': 3301, 'incorporate': 4599, 'padding': 6485, 'displaying': 2673, 'nina': 6159, 'jury': 4969, 'mores': 5933, 'circa': 1707, 'armed': 622, 'slaves': 8207, 'irreverent': 4820, 'wider': 9809, 'irs': 4826, 'ludicrously': 5414, 'marketed': 5561, 'aspiring': 671, 'rapidly': 7200, '90s': 153, 'rhys': 7521, 'ifans': 4493, 'fiennes': 3433, 'shouting': 8088, 'fitzgerald': 3501, 'morricone': 5944, 'spaghetti': 8352, 'lemmon': 5200, 'maker': 5493, 'owes': 6464, 'novak': 6222, 'vertigo': 9525, 'ernie': 3108, 'kovacs': 5075, 'gingold': 3843, 'laurel': 5154, 'split': 8402, 'venture': 9515, 'stooges': 8549, 'tangled': 8839, 'serum': 7947, 'expresses': 3270, 'feast': 3383, 'lands': 5118, 'fireplace': 3484, 'tumbling': 9276, 'greenhouse': 3997, 'projection': 7003, 'screens': 7836, 'offbeat': 6304, 'prolific': 7006, 'glee': 3863, 'roach': 7575, 'enormous': 3064, 'boost': 1163, 'shield': 8044, 'enhanced': 3056, 'jan': 4863, 'cruelty': 2215, 'confirmed': 1954, 'healthy': 4188, 'maher': 5479, 'intellect': 4724, 'assertion': 679, 'stare': 8467, 'hmmm': 4315, 'islam': 4829, 'liberal': 5237, 'fellini': 3401, 'biased': 1032, 'interlude': 4754, 'annamarie': 515, 'closure': 1779, 'informative': 4648, 'theirs': 8954, 'rack': 7151, 'bravery': 1225, 'muslim': 6019, 'lesbians': 5214, 'tackle': 8811, 'appreciation': 590, 'reflected': 7308, 'impending': 4544, 'harlow': 4138, 'eadie': 2896, 'patsy': 6582, 'kitty': 5051, 'missouri': 5847, 'gift': 3825, 'lionel': 5289, 'declares': 2381, 'listed': 5295, 'pendleton': 6613, 'downtown': 2780, 'griffith': 4004, 'intolerance': 4770, 'criticisms': 2193, 'sections': 7875, 'las': 5132, 'vegas': 9507, 'strives': 8598, 'exposing': 3265, 'intricate': 4771, 'stevens': 8526, 'mozart': 5981, 'luc': 5401, 'chuck': 1692, 'sketch': 8184, 'ian': 4467, 'rocks': 7604, 'spree': 8424, 'counter': 2105, 'slew': 8217, 'goofs': 3927, 'loopholes': 5359, 'vow': 9624, 'brashear': 1222, 'admitted': 272, 'diver': 2699, 'ledger': 5187, 'helicopter': 4224, 'goldsworthy': 3912, 'letting': 5229, 'smallest': 8242, 'greatly': 3989, 'portrayals': 6827, 'katie': 4990, 'comparisons': 1899, 'trashed': 9186, 'claimed': 1720, 'concentrate': 1929, 'actuality': 239, 'rosario': 7646, 'displayed': 2672, 'maya': 5634, 'region': 7324, 'motorcycle': 5963, 'genders': 3774, 'remained': 7369, 'slim': 8225, 'drowned': 2838, 'cigarette': 1700, 'diving': 2707, 'audio': 751, 'wide': 9807, 'smartly': 8245, 'relatives': 7346, 'spoken': 8411, 'hebrew': 4211, 'observes': 6268, 'strive': 8597, 'astute': 711, 'hype': 4457, 'enormously': 3065, 'layered': 5164, 'chainsaw': 1563, 'narratives': 6060, 'premiered': 6899, 'antonio': 544, 'trivia': 9244, 'melissa': 5702, 'negligible': 6108, 'adulterous': 282, 'titular': 9067, 'participation': 6544, 'bloom': 1114, 'marathon': 5535, 'languages': 5125, 'legal': 5193, 'depending': 2468, 'insects': 4677, 'uma': 9319, 'thurman': 9027, 'washing': 9694, 'desk': 2512, 'surround': 8748, 'ensues': 3069, 'shooter': 8067, 'babes': 803, 'um': 9318, 'bout': 1194, 'apologies': 568, 'rodriguez': 7611, 'girlfight': 3845, 'darn': 2321, 'adrian': 280, 'areas': 610, 'anger': 495, '69': 142, 'dives': 2704, 'marked': 5559, 'medieval': 5683, 'quotes': 7141, 'catherine': 1517, 'flies': 3535, 'tripping': 9237, 'addiction': 251, 'capacity': 1430, 'charlotte': 1603, 'roughly': 7656, 'rep': 7401, 'btw': 1292, 'diane': 2564, 'adored': 279, 'addicted': 250, 'thelma': 8955, 'louise': 5380, 'vulgar': 9628, 'incapable': 4575, 'caper': 1432, 'stupidest': 8635, 'warped': 9684, 'dont': 2749, 'wrath': 9923, 'conveying': 2050, 'dorff': 2760, 'troops': 9251, 'drums': 2845, 'difficulty': 2585, 'shifting': 8046, 'suggested': 8685, 'ostensibly': 6415, 'reward': 7513, 'trent': 9214, 'unsympathetic': 9424, 'insults': 4719, 'heartland': 4201, 'gate': 3758, 'fraction': 3636, 'joys': 4941, 'anarene': 475, 'closes': 1775, 'bridges': 1248, 'shepherd': 8037, 'meg': 5694, 'fetched': 3415, 'esque': 3122, 'insulted': 4716, 'division': 2708, 'viewpoint': 9558, 'begs': 954, 'opinions': 6370, 'noam': 6170, 'jerusalem': 4894, 'lighthearted': 5257, 'rabbits': 7144, 'intensely': 4734, 'lydia': 5439, 'brennan': 1242, 'amos': 456, 'purchased': 7088, 'bless': 1096, 'departed': 2462, 'pranks': 6872, 'crooks': 2200, 'determine': 2534, 'installment': 4697, 'remembering': 7381, 'assured': 701, 'coverage': 2126, 'basics': 879, 'unrelated': 9410, 'conception': 1934, 'attract': 741, 'adventures': 291, 'immediate': 4533, 'arguments': 616, 'holden': 4323, 'advise': 297, 'caution': 1527, 'chess': 1633, 'forewarned': 3599, 'versus': 9524, 'reviewing': 7505, 'illuminate': 4508, 'skull': 8197, 'outta': 6442, 'boasts': 1129, 'burial': 1330, 'assures': 702, 'freshness': 3673, 'identified': 4481, 'semester': 7906, 'angst': 502, 'lynch': 5442, '98': 156, 'deathtrap': 2361, 'definition': 2408, 'reeve': 7300, 'joined': 4922, 'veterans': 9528, 'taxi': 8863, 'pigs': 6707, 'flawed': 3519, 'vanishing': 9491, 'niece': 6151, 'dropped': 2834, 'hammer': 4097, 'sinatra': 8150, 'maclaine': 5455, 'nuts': 6244, 'brawl': 1227, 'vivid': 9604, 'progresses': 6999, 'worthless': 9913, 'aisle': 359, 'observed': 6266, 'excesses': 3194, '1951': 46, 'overhead': 6453, 'avoids': 782, 'lean': 5174, 'pirates': 6718, 'moulin': 5964, 'poitier': 6786, 'pathological': 6573, 'grayson': 3984, 'mercy': 5739, 'operatic': 6365, 'agony': 337, 'questionable': 7127, 'niven': 6167, 'relentless': 7351, 'olds': 6334, 'impersonating': 4545, 'envy': 3093, 'gut': 4055, 'utopia': 9470, 'lowered': 5393, 'deaf': 2349, 'matte': 5619, 'belly': 982, 'metal': 5761, 'headache': 4179, 'email': 2998, 'plausible': 6748, 'valley': 9483, 'voted': 9622, 'amanda': 432, 'affection': 308, 'colbert': 1812, 'toronto': 9110, 'intentionally': 4739, 'husbands': 4451, 'iran': 4807, 'soccer': 8274, 'challenged': 1566, 'iron': 4813, 'fish': 3491, 'directs': 2620, 'bard': 855, 'wayward': 9717, 'nails': 6045, 'summation': 8701, 'wonders': 9882, 'sidney': 8115, '1973': 67, 'frankenheimer': 3651, 'scheider': 7799, 'trebor': 9204, 'raped': 7198, 'preston': 6919, 'se': 7851, 'ragged': 7157, 'filth': 3460, 'examination': 3180, 'viewings': 9557, 'renegade': 7395, 'fulfilling': 3702, 'vu': 9627, 'recurring': 7286, 'escaped': 3115, 'fabric': 3291, 'conveyor': 2051, 'emergence': 3006, 'coat': 1799, 'simmons': 8139, 'shipman': 8052, 'maxwell': 5632, 'parodies': 6536, 'mack': 5454, 'imitating': 4529, 'anita': 512, '1917': 22, 'jj': 4909, 'critic': 2189, 'overbearing': 6447, 'tomba': 9084, 'quarters': 7120, 'destructive': 2526, '1993': 89, 'velvet': 9511, 'huppert': 4443, 'wwi': 9944, 'instincts': 4706, 'brady': 1211, 'bird': 1060, 'paulie': 6588, 'parrot': 6538, 'pesci': 6656, 'robbins': 7588, 'farm': 3350, 'fought': 3626, 'beggars': 947, 'horses': 4380, 'beans': 909, 'moorehead': 5919, 'wagner': 9633, 'lange': 5123, 'hairstyles': 4078, 'residence': 7447, 'rope': 7645, 'morally': 5928, 'depict': 2470, 'phones': 6676, 'gunned': 4050, 'preparation': 6902, 'confronted': 1959, 'peck': 6606, 'ruthlessly': 7703, 'yankovic': 9954, 'mockumentary': 5870, 'vignettes': 9562, 'longest': 5350, 'suggesting': 8686, 'campers': 1405, 'santa': 7754, 'darkheart': 2317, 'eh': 2961, 'voiced': 9611, 'richly': 7529, 'slam': 8199, 'hurricane': 4446, 'tearjerker': 8874, 'er': 3103, 'relation': 7340, 'naval': 6083, 'abhorrent': 164, 'admirable': 263, 'lay': 5163, 'pathos': 6574, '1934': 31, 'immersed': 4537, 'conniving': 1975, 'sleeps': 8213, 'broad': 1264, 'reversed': 7500, 'retired': 7483, 'benjamin': 997, 'monumental': 5911, 'valentine': 9479, 'vaudeville': 9502, 'potato': 6852, 'chip': 1660, 'cheh': 1627, 'lizard': 5314, 'battles': 897, 'muffled': 5991, 'shaw': 8025, 'establishment': 3130, 'sophia': 8322, 'loren': 5365, 'canvas': 1425, 'shakes': 7996, 'newer': 6134, 'alpha': 415, 'eighth': 2964, 'characterization': 1592, 'goldie': 3910, 'hawn': 4171, 'duration': 2876, 'revolver': 7511, 'ecstasy': 2925, 'richie': 7528, 'row': 7664, 'brained': 1213, 'comparing': 1897, 'uptight': 9452, 'confidence': 1951, 'dench': 2446, 'widow': 9811, 'alimony': 391, 'holm': 4333, 'caron': 1474, 'bass': 884, 'intelligently': 4729, 'inventive': 4789, 'belong': 983, 'italy': 4842, 'babe': 802, 'furniture': 3716, 'chicago': 1639, 'secular': 7876, 'travolta': 9196, 'pam': 6508, 'implies': 4548, 'anyways': 558, 'korea': 5073, 'gojoe': 3905, 'jewish': 4903, 'stupider': 8634, 'cartwright': 1492, 'bartender': 869, 'females': 3406, 'blunt': 1121, 'invariably': 4784, 'talentless': 8827, 'objects': 6255, 'sanjay': 7750, 'deveraux': 2544, 'controls': 2038, 'breed': 1240, 'slips': 8229, 'secure': 7877, 'poetic': 6777, 'furious': 3715, 'scratched': 7825, 'repertoire': 7408, 'distribution': 2692, 'uncredited': 9334, 'shapiro': 8014, 'zany': 9989, 'chevy': 1636, 'belzer': 990, 'spoofing': 8414, 'cooking': 2065, 'dealers': 2352, 'influential': 4644, 'shadows': 7989, 'unnerving': 9399, 'soles': 8291, 'waist': 9635, 'copyright': 2075, 'posted': 6847, 'html': 4402, 'paragraph': 6523, 'blank': 1085, 'disgruntled': 2656, 'serviceable': 7954, 'summoned': 8703, 'telephone': 8896, 'anchor': 477, 'forgivable': 3602, 'conveyed': 2049, 'courage': 2118, 'mcadams': 5638, 'murphy': 6010, 'tick': 9032, 'operating': 6366, 'lethargic': 5225, 'beware': 1028, 'coupled': 2116, 'ponder': 6802, 'uncreative': 9333, 'mismatched': 5840, 'rescues': 7438, 'gypo': 4061, 'gracefully': 3953, 'starving': 8483, 'alternating': 424, 'explicitly': 3246, '1929': 27, 'associates': 691, 'ny': 6247, 'obscene': 6260, 'corn': 2079, 'conspiracy': 1996, 'uniforms': 9375, 'corrupt': 2091, 'blatant': 1087, 'theories': 8963, 'viet': 9549, 'nam': 6048, 'madhur': 5462, 'bhandarkar': 1031, 'endlessly': 3040, 'parties': 6547, 'sharma': 8021, 'hostess': 4384, 'pearl': 6605, 'diversions': 2702, 'rotten': 7652, 'couch': 2101, 'hunger': 4434, 'benign': 996, 'bites': 1068, 'societal': 8277, 'involve': 4801, 'fur': 3714, '1979': 73, 'psychologically': 7059, 'sans': 7752, 'valerie': 9480, 'quincy': 7134, 'ba': 801, 'battlefield': 896, 'dramatically': 2800, 'norma': 6194, 'berkeley': 1004, 'sober': 8273, 'suspension': 8766, 'forgiving': 3605, 'messing': 5758, 'citizen': 1713, 'vincent': 9573, 'banter': 848, 'exit': 3217, 'hmm': 4314, 'asset': 681, 'offend': 6306, 'protracted': 7035, 'thru': 9023, 'bete': 1015, 'notoriety': 6219, 'anticipated': 538, 'click': 1756, 'subtly': 8658, 'bean': 908, 'comeback': 1849, 'flexible': 3532, 'poo': 6804, 'weakness': 9721, 'enemy': 3045, 'miraglia': 5827, 'evelyn': 3149, 'intact': 4721, 'motive': 5961, 'truely': 9259, 'stargate': 8469, 'coke': 1810, 'ingenious': 4654, 'bio': 1056, 'golf': 3914, 'altering': 420, 'julie': 4957, 'debbie': 2364, 'hideous': 4269, 'devoid': 2550, 'morton': 5948, 'raptor': 7202, 'miscasting': 5832, 'jedi': 4882, 'rousing': 7660, 'saga': 7721, 'falcon': 3322, 'willingly': 9826, 'seventh': 7968, 'neill': 6113, 'letdown': 5223, 'da': 2272, 'priests': 6943, 'viking': 9564, 'hats': 4162, 'vikings': 9565, 'juan': 4943, '1948': 42, 'hara': 4130, 'buccaneer': 1294, 'pirate': 6717, 'preceded': 6879, 'flags': 3506, 'vintage': 9575, 'caribbean': 1460, 'incidentally': 4581, 'remade': 7366, 'doug': 2770, 'mcclure': 5641, 'unprecedented': 9403, 'consisted': 1992, '1952': 47, 'gods': 3896, 'switched': 8789, 'profile': 6989, 'storm': 8558, 'katsu': 4991, 'lone': 5345, 'hanzo': 4118, 'razor': 7222, 'ninjas': 6164, 'shady': 7990, 'treasury': 9198, 'utilized': 9469, 'nerd': 6120, 'predict': 6886, 'pokes': 6788, 'orgy': 6400, 'fraggle': 3637, 'fourteen': 3631, 'playful': 6753, 'inhabited': 4659, 'plants': 6745, 'gobo': 3890, 'automobiles': 773, 'excitement': 3198, 'squad': 8431, 'raines': 7164, 'memphis': 5721, 'nicolas': 6149, 'bandits': 841, 'duvall': 2883, 'patton': 6585, 'earned': 2904, 'cannibal': 1419, 'bloodthirsty': 1112, 'lungs': 5430, 'gwyneth': 4060, 'paltrow': 6507, 'vastly': 9501, 'clueless': 1787, 'buff': 1303, 'postman': 6850, 'mara': 5534, 'unbeknownst': 9325, 'eater': 2920, 'investigator': 4795, 'skippy': 8194, 'upset': 9450, 'mockery': 5868, 'progressive': 7000, 'colonial': 1828, 'passions': 6564, 'porter': 6821, 'nun': 6240, 'mae': 5469, 'nigel': 6153, 'rushes': 7695, 'burned': 1334, 'remainder': 7368, 'trial': 9215, 'lunatic': 5426, 'marcello': 5537, 'bogart': 1137, 'luis': 5417, 'clunky': 1791, 'jersey': 4893, 'angie': 497, 'carell': 1456, 'rogen': 7613, 'shelley': 8034, 'electronics': 2976, 'vivacious': 9601, 'raunchy': 7216, 'astoundingly': 707, 'objectively': 6254, 'ruben': 7671, 'jewison': 4904, 'breakdancing': 1230, '1984': 79, 'hugely': 4407, 'heartwarming': 4203, 'gap': 3746, 'june': 4965, 'allyson': 408, 'hoover': 4357, 'kolchak': 5069, 'mcgavin': 5649, 'fonda': 3573, 'courtroom': 2122, 'todd': 9071, 'generate': 3778, 'stunk': 8628, 'keyboard': 5014, 'omg': 6347, 'freaks': 3659, 'ilk': 4502, 'income': 4590, 'hug': 4405, 'midget': 5782, 'prominent': 7007, 'brando': 1219, 'waterfront': 9708, 'vivian': 9603, 'rockin': 7602, 'dyke': 2890, 'mannered': 5524, 'crosses': 2204, 'followers': 3568, 'survived': 8754, 'volunteer': 9617, 'blob': 1102, 'excellently': 3186, 'anthology': 534, 'bromwell': 1270, 'programs': 6996, '23': 114, 'beef': 937, 'announcer': 520, 'penis': 6616, 'glued': 3885, 'stripping': 8596, 'passages': 6558, 'marijuana': 5549, 'lane': 5121, 'freak': 3657, 'participate': 6542, 'overdone': 6452, 'hahk': 4072, 'tolerable': 9078, 'cabaret': 1371, 'asia': 660, 'techno': 8882, 'possibilities': 6842, 'perception': 6624, 'anticipation': 539, 'dot': 2764, 'costuming': 2099, 'apologize': 569, 'summarize': 8699, 'locks': 5332, 'binder': 1055, 'irritated': 4823, 'interaction': 4744, 'discussed': 2649, 'studies': 8620, 'replay': 7414, 'injustice': 4668, 'insisting': 4687, 'egotistical': 2958, 'amnesia': 451, 'unrated': 9405, 'alibi': 383, 'murderers': 6006, 'cuteness': 2262, 'courtesy': 2121, 'broderick': 1267, 'renoir': 7396, 'regarded': 7318, 'femme': 3409, 'fatale': 3367, 'nana': 6054, 'companion': 1891, 'memoirs': 5715, 'wives': 9868, 'deliberate': 2414, 'suitors': 8695, 'elegance': 2977, 'werner': 9759, 'tinted': 9057, 'atwill': 746, 'mabel': 5446, 'begged': 948, 'barn': 862, 'robbers': 7585, 'barrier': 865, 'danes': 2298, 'othello': 6416, 'iago': 4466, 'fishburne': 3492, 'refuse': 7314, 'barbarian': 851, 'gingerbread': 3842, 'cape': 1431, 'kidnapped': 5024, 'returned': 7487, 'righteous': 7542, 'deplorable': 2476, 'hunting': 4442, 'murderous': 6008, 'counterpoint': 2106, 'approaching': 593, 'account': 208, 'cher': 1632, 'moonstruck': 5917, 'id': 4473, 'rendered': 7392, 'admiration': 265, 'illusion': 4509, 'spaceship': 8348, 'ounce': 6421, 'meditation': 5686, 'buried': 1331, 'horrendous': 4370, 'dazzled': 2341, 'overwhelming': 6462, 'suspicion': 8767, 'controlling': 2037, 'partially': 6540, 'wright': 9930, 'composer': 1919, 'dignity': 2591, 'divorced': 2710, 'villainous': 9570, 'gomez': 3915, 'elisha': 2986, 'cornell': 2080, 'plotting': 6769, 'assist': 685, 'minions': 5814, 'maltese': 5503, 'reunited': 7492, 'developments': 2542, 'arquette': 629, 'conscious': 1981, 'corners': 2082, 'unscathed': 9416, 'angels': 494, 'clips': 1765, 'dozens': 2784, 'excuses': 3204, 'faster': 3364, 'wrenching': 9925, 'ambiance': 439, 'vietnamese': 9551, 'bell': 979, 'candle': 1416, 'sweetheart': 8781, 'henderson': 4242, 'circle': 1708, 'merle': 5747, 'spell': 8379, 'manners': 5526, 'greenwich': 3998, 'wolfe': 9871, 'elsa': 2992, 'lanchester': 5114, 'unusually': 9432, 'fey': 3421, 'kaufman': 4992, 'stiller': 8535, 'antonioni': 545, 'daria': 2311, 'floyd': 3550, 'cancelled': 1414, 'combines': 1845, 'matches': 5612, 'instrumental': 4712, 'transportation': 9179, 'bye': 1367, 'waits': 9640, 'insanity': 4675, 'launch': 5151, 'scooby': 7816, 'doo': 2750, 'disgraceful': 2655, 'pocket': 6773, 'microfilm': 5778, 'antiques': 541, 'toupee': 9127, 'tina': 9055, 'chen': 1631, 'suave': 8643, 'redford': 7293, 'wardrobe': 9671, 'jacket': 4851, 'dunaway': 2871, 'cunning': 2240, 'moody': 5914, 'fence': 3410, 'lester': 5221, 'commend': 1868, 'scrooge': 7849, 'sellers': 7902, 'randomly': 7183, 'illustrate': 4511, 'rodder': 7609, 'carlos': 1466, 'mencia': 5725, 'jabs': 4849, 'hooked': 4353, 'sant': 7753, 'towers': 9135, 'meter': 5764, 'disservice': 2676, 'teddy': 8886, 'martha': 5578, 'vivah': 9602, 'shahid': 7994, 'amrita': 461, 'menu': 5735, 'mendes': 5726, 'representative': 7422, 'whipping': 9793, 'garage': 3747, 'activity': 232, 'bridget': 1249, 'aiello': 347, 'gradually': 3957, 'contributed': 2031, 'grass': 3976, 'prostitution': 7028, 'moose': 5920, 'gielgud': 3824, 'demeanor': 2434, 'bon': 1149, 'jovi': 4938, 'arly': 620, 'jover': 4937, 'complaints': 1910, 'reaching': 7228, 'flames': 3509, 'mormons': 5938, 'hyrum': 4462, 'rejection': 7335, 'opposition': 6377, 'moviegoers': 5978, 'barrage': 863, 'splendid': 8401, 'obstacle': 6273, 'muni': 6001, 'wang': 9661, 'lung': 5429, 'luise': 5418, 'rainer': 7163, 'lan': 5112, 'realizing': 7250, 'worn': 9906, 'passage': 6557, 'seventy': 7970, 'trippy': 9238, 'glenn': 3865, 'norman': 6197, 'kane': 4978, 'distinctly': 2683, 'commodity': 1883, 'crowe': 2208, 'burnt': 1337, 'olen': 6336, 'poe': 6775, 'scarecrows': 7787, 'occurrences': 6288, 'psychopath': 7062, 'snow': 8269, 'politicians': 6797, 'crashes': 2144, 'pancake': 6512, 'transmitted': 9176, 'diagnosis': 2556, 'awarded': 787, 'justification': 4972, 'gloria': 3873, 'tibetan': 9031, 'climb': 1761, 'sighted': 8118, 'subsequently': 8652, 'goals': 3888, 'desires': 2511, 'assessment': 680, 'indestructible': 4611, 'miraculously': 5826, 'monday': 5890, 'saura': 7772, 'quintessential': 7136, 'surroundings': 8751, 'irritate': 4822, 'confronts': 1960, 'bounty': 1193, 'android': 488, 'alienator': 388, 'bowie': 1196, 'shapes': 8013, '3000': 123, 'tire': 9060, 'snakes': 8258, 'injured': 4666, 'airplane': 357, 'socialist': 8276, 'finance': 3465, 'dominating': 2742, 'definitive': 2409, 'carlito': 1465, 'rambo': 7177, 'glamor': 3855, 'ripping': 7557, 'mist': 5848, 'outdated': 6427, 'jfk': 4906, 'protection': 7032, 'flair': 3507, 'glowing': 3883, 'yard': 9955, 'marrying': 5573, 'undertones': 9352, 'pillow': 6709, 'spiderman': 8387, 'glitch': 3870, 'update': 9443, 'scored': 7818, 'muscle': 6012, 'skinned': 8191, 'knotts': 5062, 'delighted': 2420, 'stares': 8468, 'cheaply': 1616, 'holocaust': 4335, 'gambit': 3737, 'considerably': 1987, 'dome': 2736, 'knock': 5059, 'mannequin': 5522, 'meryl': 5751, 'streep': 8577, 'phantasm': 6663, 'duh': 2862, 'eleven': 2985, 'northam': 6200, 'companies': 1890, 'rita': 7566, 'nifty': 6152, 'spawn': 8361, 'pages': 6487, 'booth': 1165, 'rightfully': 7543, 'chaplin': 1586, 'nightmares': 6157, 'foxx': 3634, 'thugs': 9024, 'grendel': 4000, 'announcement': 519, 'beowulf': 1001, 'poem': 6776, 'refused': 7315, 'helmets': 4232, 'marina': 5550, 'tables': 8808, 'mullet': 5994, 'ingrid': 4656, 'peters': 6660, 'sank': 7751, 'harm': 4139, 'scratches': 7826, 'deck': 2380, 'fido': 3429, 'timmy': 9053, 'resurrected': 7478, 'radiation': 7152, 'moss': 5949, 'esquire': 3123, 'constance': 1997, 'unsure': 9422, 'redgrave': 7294, 'gardener': 3751, 'shack': 7986, 'inhabit': 4657, 'traits': 9163, 'experimental': 3234, 'tucker': 9275, 'puberty': 7064, 'airing': 356, 'splatter': 8400, 'nr': 6231, 'inducing': 4626, 'hotter': 4388, 'violently': 9579, 'shares': 8018, 'mistreated': 5853, 'deconstructed': 2384, 'spouse': 8422, 'caretaker': 1458, 'ourselves': 6423, 'environmental': 3092, 'esteem': 3132, 'retire': 7482, 'spilling': 8391, 'sided': 8110, 'muslims': 6020, 'hadith': 4068, 'christianity': 1683, 'bombing': 1147, 'entirety': 3087, 'quantum': 7118, 'weed': 9736, 'sparkles': 8359, 'anxiety': 548, 'dismissed': 2668, 'shift': 8045, 'principle': 6953, 'achieves': 217, 'israel': 4834, 'communication': 1886, 'jews': 4905, 'tanya': 8842, 'hamill': 4094, 'affleck': 312, 'herd': 4246, 'fills': 3452, 'deniro': 2449, 'ongoing': 6354, 'ruiz': 7681, 'calmly': 1389, 'alternately': 422, 'swift': 8783, 'countess': 2107, 'tremendously': 9210, 'incorporates': 4600, 'ruled': 7683, 'lafitte': 5102, 'yul': 9986, 'brynner': 1290, 'adviser': 299, 'governor': 3944, 'bradley': 1210, 'decoration': 2385, 'mounted': 5967, 'alienation': 387, 'vittorio': 9600, 'benefit': 994, 'disturb': 2695, 'beckinsale': 929, 'samantha': 7738, 'knightley': 5056, 'excepting': 3188, 'olivia': 6339, 'forum': 3621, 'disasters': 2634, 'conquers': 1977, 'biography': 1057, 'columbia': 1836, 'showcases': 8092, 'hayworth': 4175, 'bannister': 847, 'everett': 3157, 'helpless': 4237, 'grisby': 4008, 'ploy': 6770, 'suitably': 8693, 'romantically': 7626, 'reflects': 7312, 'reagan': 7238, 'troublesome': 9256, 'forwarded': 3623, 'hobbits': 4317, 'aragorn': 600, 'ranger': 7187, 'viggo': 9560, 'mortensen': 5947, 'gandalf': 3740, 'orcs': 6391, 'humanoid': 4421, 'mouths': 5971, 'immersion': 4538, 'ash': 656, 'mccrea': 5645, 'hunk': 4436, 'disgust': 2659, 'poppins': 6813, 'ghostly': 3816, 'commanding': 1866, 'capt': 1438, 'dillman': 2594, 'gen': 3772, 'supply': 8725, 'unfold': 9366, 'penalty': 6612, 'incestuous': 4577, 'lump': 5425, 'appallingly': 572, 'abandon': 160, 'gershwin': 3806, 'levant': 5230, 'bickering': 1035, 'claus': 1738, 'pet': 6657, 'blooded': 1110, 'gabriel': 3725, 'parable': 6520, 'hernandez': 4250, 'lengthy': 5206, 'puff': 7068, 'rural': 7692, 'adultery': 283, 'milland': 5796, 'caprica': 1436, 'nausicaa': 6082, 'possession': 6841, 'gail': 3731, 'strangler': 8571, '19': 19, 'button': 1361, 'insomnia': 4689, 'gandolfini': 3741, 'rolls': 7622, 'greek': 3994, 'casablanca': 1494, 'compete': 1903, 'dreadfully': 2809, 'letters': 5228, 'gig': 3828, 'invasion': 4785, 'cate': 1515, 'disappoints': 2632, 'pretentiousness': 6927, 'sherlock': 8040, 'augustus': 756, 'milverton': 5802, 'servant': 7948, 'cushing': 2257, 'sophie': 8323, 'frye': 3697, 'bats': 894, 'resemblance': 7441, 'grudge': 4026, 'strickland': 8586, 'enthusiastic': 3084, 'instruction': 4709, 'inc': 4574, 'swimming': 8785, 'myles': 6030, 'berkowitz': 1005, 'andreeff': 485, 'hybrid': 4455, 'diamonds': 2562, 'oklahoma': 6329, 'drain': 2795, 'grease': 3985, 'aesthetic': 301, 'harrison': 4146, 'fleeting': 3528, 'omar': 6345, 'blamed': 1083, 'mills': 5801, 'billie': 1049, 'exorcist': 3218, 'charley': 1601, 'mcgregor': 5651, 'collar': 1817, 'canal': 1411, 'supermarionation': 8719, 'indicated': 4617, 'thunderbirds': 9026, 'pistols': 6719, 'morons': 5943, 'scratching': 7827, 'howling': 4401, 'criticized': 2194, 'lycanthrope': 5438, 'gimmicky': 3839, 'eleanor': 2973, 'cagney': 1375, 'goody': 3925, 'denying': 2458, 'natalie': 6067, 'audrey': 753, 'manager': 5511, 'jenny': 4888, 'hartley': 4151, 'idiosyncrasies': 4486, 'espionage': 3121, 'annoyingly': 525, 'affecting': 307, 'spectrum': 8374, 'curve': 2255, 'pause': 6589, 'grams': 3963, 'beirut': 968, 'bogey': 1138, 'tierney': 9037, 'masked': 5590, 'ppv': 6866, 'wrestlers': 9927, 'wwe': 9943, 'championship': 1571, 'cena': 1545, 'rvd': 7704, 'streak': 8575, 'triple': 9236, 'whimsical': 9788, 'dahmer': 2278, 'sandy': 7746, 'www': 9946, 'becky': 930, 'charms': 1607, 'pot': 6851, 'predicament': 6885, 'fuzzy': 3722, 'antonietta': 543, 'cruella': 2214, 'modification': 5877, 'dalmatians': 2281, 'signature': 8122, 'indicates': 4618, 'fetchit': 3416, 'hyped': 4458, 'joins': 4924, 'helmed': 4230, 'cube': 2228, 'choir': 1665, 'befriend': 943, 'nod': 6173, 'lindsey': 5279, 'request': 7430, 'devotion': 2553, 'assortment': 693, 'skinny': 8192, 'mobile': 5865, 'fenway': 3411, 'appreciating': 589, 'anchorman': 479, 'backstage': 815, 'shell': 8033, 'goldwyn': 3913, 'tobias': 9069, 'preview': 6934, 'fugitive': 3700, 'snitch': 8266, 'cahill': 1376, 'insights': 4682, 'psyche': 7052, 'hastily': 4155, 'estate': 3131, 'pilots': 6712, 'beginners': 951, 'sparkle': 8358, 'theft': 8952, 'flashy': 3515, 'suzette': 8772, '20s': 109, 'apathy': 563, 'explodes': 3248, 'welcomed': 9746, 'bearable': 911, 'roots': 7644, 'esther': 3133, 'evans': 3147, 'walker': 9648, 'penny': 6618, 'baddies': 820, 'meandering': 5661, 'relive': 7361, 'drifting': 2822, 'suggestive': 8688, 'melancholy': 5699, 'hay': 4172, 'determination': 2533, 'informs': 4651, 'invested': 4791, 'byron': 1368, 'strummer': 8611, 'limitations': 5273, 'ceiling': 1534, 'doe': 2724, 'intends': 4732, 'shocker': 8059, 'oberon': 6251, 'harbor': 4131, 'avoided': 780, 'artemisia': 643, 'gackt': 3726, 'frequent': 3669, 'jess': 4895, 'franco': 3649, 'sales': 7731, 'madman': 5465, 'gruner': 4029, 'lurking': 5434, 'tourists': 9130, 'wan': 9658, 'creed': 2171, 'ludlow': 5415, 'jud': 4944, 'crypt': 2225, 'axe': 799, 'succession': 8668, 'congratulations': 1966, 'dipping': 2609, 'preminger': 6900, 'dana': 2291, 'quotable': 7139, 'dixon': 2712, 'distinction': 2681, 'imprisoned': 4562, 'doodlebops': 2752, 'oppressed': 6378, 'censorship': 1547, 'voters': 9623, 'collora': 1826, 'hearn': 4193, 'kent': 5008, 'cheezy': 1626, 'lois': 5340, 'teaming': 8872, 'bug': 1306, 'dreamworks': 2813, 'ajay': 361, 'enchanting': 3028, 'herein': 4248, 'bronte': 1272, 'carlton': 1467, 'browne': 1283, 'amphibulos': 459, 'dirt': 2621, 'gaillardia': 3732, 'height': 4215, 'throne': 9015, 'addressed': 257, 'mice': 5773, 'jaq': 4872, 'stepsisters': 8517, 'marred': 5568, 'lucifer': 5405, 'didnt': 2571, 'unthoughtful': 9427, 'sexist': 7976, 'helluva': 4229, 'culprit': 2234, 'assassinate': 674, 'sentinel': 7932, 'subplots': 8650, 'vincenzo': 9574, 'risking': 7563, 'occurring': 6289, 'tourist': 9129, 'egypt': 2959, 'covering': 2128, 'mastered': 5600, 'formulaic': 3614, 'vida': 9545, 'portugal': 6831, 'hack': 4065, 'throwaway': 9019, 'solitude': 8294, 'talkie': 8833, 'marx': 5585, 'feisty': 3399, 'items': 4844, 'pyramid': 7111, 'odyssey': 6299, 'classy': 1736, 'kaakha': 4977, 'observing': 6269, 'sleeper': 8211, 'cheers': 1623, 'edel': 2928, 'anchored': 478, 'zoe': 9994, 'interchangeable': 4746, 'convenient': 2040, 'drum': 2843, 'tingler': 9056, 'dante': 2308, 'boots': 1167, 'distraction': 2690, 'tripe': 9235, 'chopper': 1671, 'sunset': 8709, 'gifted': 3826, '345': 126, 'ond': 6351, 'ej': 2968, 'hanka': 4115, 'jakub': 4859, 'shockingly': 8061, 'paz': 6597, 'vega': 9506, 'detour': 2536, 'yakuza': 9952, 'bandwagon': 843, 'user': 9463, 'mcgrath': 5650, 'antagonist': 533, 'trackers': 9143, 'journeymen': 4936, 'pickford': 6693, 'reflections': 7311, 'silverman': 8133, 'cambodia': 1393, 'trafficking': 9152, '85': 150, 'yikes': 9969, 'skid': 8185, '48': 134, 'cowardly': 2130, 'commits': 1879, 'juice': 4954, 'fiend': 3432, 'hugo': 4413, 'ss': 8437, 'contemporaries': 2008, 'figuring': 3447, 'teresa': 8914, 'rajinikanth': 7172, 'glaring': 3859, 'inconsistencies': 4597, 'dbd': 2343, 'mesmerizing': 5753, 'nite': 6166, 'pursuit': 7101, 'pei': 6611, 'triumphant': 9243, 'dietrichson': 2577, 'neff': 6103, 'trips': 9239, 'prop': 7017, 'stepmother': 8514, 'inexplicable': 4635, 'untalented': 9425, 'hallucinations': 4090, 'hallucination': 4089, '43': 132, 'whore': 9803, 'rotting': 7653, 'scurry': 7850, 'divided': 2705, 'yorkers': 9972, 'lamb': 5107, 'whims': 9787, 'cassie': 1500, 'dreamed': 2811, 'retirement': 7484, 'dynamic': 2892, 'plummer': 6771, 'helsing': 4239, 'vault': 9503, 'odin': 6298, 'berserkers': 1009, 'scorned': 7820, 'boar': 1124, 'barek': 857, 'ala': 366, 'funhouse': 3709, 'haphazard': 4119, 'concludes': 1942, 'astonished': 704, 'seed': 7882, 'intruder': 4782, 'wheelchair': 9773, 'invincible': 4797, 'stalked': 8449, 'lana': 5113, 'microphone': 5779, 'marquez': 5567, 'rub': 7668, 'baloo': 835, 'paradise': 6522, 'talespin': 8830, 'peril': 6638, 'latino': 5142, 'rookie': 7637, 'maze': 5637, 'astronauts': 710, 'spaceships': 8349, 'planes': 6739, 'blondes': 1108, 'sidekicks': 8112, 'packaging': 6480, 'childlike': 1647, 'levinson': 5233, 'soundstage': 8337, 'godmother': 3895, 'robotic': 7596, 'obligated': 6256, 'schneebaum': 7805, 'gimmick': 3837, 'montgomery': 5907, 'distrust': 2694, 'illusions': 4510, 'speeding': 8378, 'clovis': 1783, 'discs': 2647, 'denouement': 2454, 'softcore': 8283, 'kruis': 5081, 'gabe': 3724, 'abby': 162, 'chelsea': 1628, 'gigi': 3831, 'monique': 5892, 'patch': 6569, 'shantytown': 8009, 'fledged': 3524, 'visconti': 9588, 'stray': 8574, 'bicycle': 1036, 'mummy': 5998, 'brainer': 1214, 'melbourne': 5700, 'queens': 7123, 'whip': 9791, 'madison': 5463, 'stereotype': 8519, 'cain': 1377, 'incidents': 4582, 'famed': 3331, 'anupam': 547, 'crowning': 2210, 'metaphysical': 5763, 'upa': 9439, 'fronts': 3691, 'vomit': 9618, 'cringeworthy': 2184, 'hostage': 4383, 'aspires': 670, 'manhood': 5514, 'hines': 4290, 'monologue': 5898, '1890': 17, 'catastrophe': 1509, 'conceit': 1927, 'maturity': 5626, 'menzies': 5736, 'daft': 2276, 'devgan': 2545, 'hopeless': 4363, 'mulholland': 5992, '1915': 21, 'unresolved': 9413, 'bach': 806, 'solvang': 8299, 'lamm': 5110, 'ringo': 7550, 'beau': 922, 'keller': 5001, 'tub': 9273, 'scarf': 7790, 'tibet': 9030, 'harrer': 4142, 'grabbed': 3947, 'updates': 9445, 'organ': 6397, 'margin': 5544, 'patekar': 6570, 'uncut': 9335, 'sexploitation': 7977, 'discoveries': 2642, 'demonic': 2441, 'wrongly': 9938, 'buffalo': 1304, 'atari': 714, 'lured': 5433, 'glow': 3882, 'trendy': 9213, 'nymphs': 6249, 'sleeve': 8215, 'portuguese': 6832, 'frontier': 3690, 'geraldine': 3799, 'robber': 7584, 'bike': 1041, 'macintosh': 5453, 'potts': 6856, 'tremors': 9211, 'vick': 9538, 'liev': 5246, 'gis': 3848, 'rinaldi': 7547, 'cosimo': 2093, 'grabbing': 3948, 'contend': 2011, 'jang': 4866, 'meetings': 5692, 'gojitmal': 3904, 'jessie': 4898, 'bacall': 805, 'gorshin': 3934, 'newmar': 6136, 'amsterdam': 462, 'calculated': 1381, 'sherman': 8041, 'belonged': 984, 'dummy': 2868, 'sensibility': 7919, 'behaving': 959, 'schumacher': 7808, 'derision': 2487, 'sacrificing': 7711, 'simira': 8138, 'ra': 7142, 'tet': 8933, 'numar': 6235, 'egyptian': 2960, 'macek': 5449, 'jumbo': 4960, 'mecha': 5673, 'robotech': 7595, 'clouds': 1782, 'linked': 5287, 'sting': 8537, 'aim': 348, 'spells': 8380, 'tourneur': 9131, 'doris': 2761, 'dump': 2869, 'lindy': 5280, 'dingo': 2603, 'baritone': 860, 'deliverance': 2425, 'biko': 1044, 'intentioned': 4740, 'partners': 6550, 'lena': 5202, 'typing': 9309, 'medved': 5689, 'absorbed': 181, 'glenda': 3864, 'cattle': 1521, 'amusingly': 467, 'zizek': 9992, 'freudian': 3674, 'biopic': 1058, 'wee': 9735, 'illustration': 4513, 'dogma': 2728, 'brighten': 1253, 'perdition': 6625, 'receiving': 7266, 'giggle': 3830, 'sparing': 8355, 'standup': 8462, 'ida': 4474, 'lupino': 5431, 'rewarded': 7514, 'beaver': 926, 'crusade': 2219, 'somethings': 8308, 'hamburg': 4093, 'misguided': 5838, 'hallam': 4086, 'werewolves': 9758, 'cathy': 1519, 'tennis': 8909, 'diversity': 2703, 'sybil': 8792, 'danning': 2306, 'dee': 2388, 'provo': 7046, 'burgade': 1328, 'convicts': 2056, 'horny': 4369, 'whale': 9767, 'owners': 6469, 'cody': 1802, 'meantime': 5668, 'mopsy': 5922, 'ruins': 7680, 'judi': 4951, 'cylons': 2267, 'battlestar': 898, 'galactica': 3736, 'colonized': 1829, 'scenic': 7798, 'torrence': 9112, 'olive': 6337, 'molested': 5880, 'kibbutz': 5016, 'glib': 3866, 'kristel': 5078, 'repulsion': 7427, 'pullman': 7073, 'trina': 9231, 'apathetic': 562, 'carax': 1446, 'eskimo': 3118, 'mala': 5498, 'tasteful': 8857, 'sonic': 8317, 'munchies': 5999, 'ghoulies': 3818, 'graceful': 3952, 'lacey': 5092, 'miou': 5822, 'assumptions': 698, 'distorted': 2686, 'yadda': 9951, 'cultures': 2239, 'owl': 6465, 'mira': 5823, 'prodigy': 6972, 'carface': 1459, 'arcs': 606, 'analog': 471, 'controller': 2036, 'sammi': 7740, 'sabretooth': 7707, 'specials': 8368, 'boesman': 1136, 'bassett': 885, '66': 141, 'instrument': 4711, 'drool': 2832, 'macarthur': 5447, 'sargent': 7760, 'arrows': 641, 'rational': 7213, 'tycoon': 9302, 'nods': 6174, 'etcetera': 3136, 'lemon': 5201, 'snipe': 8262, 'helicopters': 4225, 'puerto': 7067, 'auntie': 758, 'disrespect': 2675, 'margret': 5546, 'oft': 6323, 'gifts': 3827, 'sleepaway': 8210, 'senile': 7912, 'luciano': 5403, 'venantino': 9513, 'venantini': 9512, 'implied': 4547, 'noon': 6190, 'cynic': 2268, 'norris': 6198, 'forbes': 3587, 'fled': 3523, 'employ': 3022, 'denholm': 2447, 'butterflies': 1360, 'roo': 7634, 'digging': 2588, 'risks': 7564, 'bolan': 1142, 'soylent': 8346, 'batmobile': 893, 'waggoner': 9632, 'alekos': 376, 'heartily': 4200, 'homer': 4340, 'mining': 5813, 'coal': 1796, 'tomatoes': 9082, 'mcnealy': 5655, 'beaches': 906, 'rockstar': 7605, 'ignores': 4498, 'thailand': 8939, 'samuel': 7741, 'moronie': 5942, 'bachelor': 807, 'lochlyn': 5329, 'kenner': 5006, 'yoshida': 9973, 'badness': 822, 'commender': 1870, 'xica': 9947, 'curses': 2251, 'mathieu': 5616, 'delirious': 2423, 'chávez': 1698, 'orca': 6388, 'monopoly': 5899, 'dudikoff': 2858, 'nope': 6191, 'deanna': 2357, 'mama': 5505, 'knightly': 5057, 'valette': 9481, 'maléfique': 5504, 'oceans': 6292, 'istanbul': 4838, 'trotta': 9252, 'holland': 4329, 'hunchback': 4429, 'soha': 8284, 'carrère': 1486, 'allure': 405, 'haliday': 4084, 'moonlighting': 5916, 'suzanne': 8771, 'vollins': 9615, 'greats': 3991, 'kells': 5002, 'maslin': 5592, 'marcie': 5540, 'hundstage': 4432, 'mcintyre': 5652, 'haim': 4075, 'bernie': 1007, 'fuqua': 3713, 'huggins': 4410, 'huggaland': 4408, 'hugsy': 4415, 'hodgepodge': 4319, 'mcdoakes': 5647, 'fontaine': 3575, 'calson': 1390, 'morris': 5945, 'krause': 5076, 'combs': 1847, 'atheists': 715, 'pavarotti': 6590, 'seberg': 7865, 'inconsistent': 4598, 'reuben': 7490, 'quigley': 7133, 'aura': 759, 'ardala': 607, 'eglantine': 2956, 'theo': 8962, 'overcomes': 6450, 'hermann': 4249, 'fassbinder': 3362, 'shakti': 8000, 'nandini': 6056, 'augusta': 755, 'snob': 8268, 'claw': 1740, 'zomcon': 9997, 'morales': 5925, 'muller': 5993, 'wheezer': 9774, '31': 125, 'germaine': 3801, 'fanfan': 3339, 'adeline': 261, 'torrance': 9111, 'melvin': 5710, 'purvis': 7102, 'erroll': 3111, 'belasco': 970, 'moby': 5866, 'ahab': 342, 'kickboxing': 5018, 'trojan': 9248, 'ajax': 360, 'notre': 6221, 'frollo': 3686, 'nastasya': 6065}


Bow train reduced vectors
[[0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]
 ...
 [0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]]


BoW validation shape
(2500, 10000)

/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function get_feature_names is deprecated; get_feature_names is deprecated in 1.0 and will be removed in 1.2. Please use get_feature_names_out instead.
  warnings.warn(msg, category=FutureWarning)

On va utiliser le MultinomialNB de scikit-learn, une implémentation du modèle Bayésien naïf. Ici, l'hypothèse naïve est que les différentes variables (mots) d'une critique sont indépendantes entre elles.

from sklearn.naive_bayes import MultinomialNB

# Create the model, train it and do the prediction 

# Build the model 
clf_multi_NB = MultinomialNB()
clf_multi_NB.fit(bow_train_splt, train_labels_splt)

predictions = clf_multi_NB.predict(bow_val_splt)

print("Predictions")
predictions

Predictions

array([1, 1, 1, ..., 1, 1, 1])

import pandas as pd
pd.DataFrame(predictions).value_counts()

1    2443
0      57
dtype: int64

from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay, classification_report

# Show the results in a readable format
print("---- Classification report ----")

report_classification = classification_report(val_labels, predictions, target_names=["positif", "negatif"], output_dict=True)

print(classification_report(val_labels, predictions, target_names=["positif", "negatif"]))

cm = confusion_matrix(val_labels, predictions)
cm_disp = ConfusionMatrixDisplay(cm, display_labels=["positif", "negatif"])

cm_disp.plot()
plt.show()

---- Classification report ----
              precision    recall  f1-score   support

     positif       0.39      0.02      0.03      1267
     negatif       0.49      0.97      0.65      1233

    accuracy                           0.49      2500
   macro avg       0.44      0.49      0.34      2500
weighted avg       0.44      0.49      0.34      2500

On peut jeter un oeil aux features construites par le vectorizer. Comment pourrait-on les améliorer ?

print(vectorizer.get_feature_names()[:100])

['avenue', 'boulevard', 'city', 'down', 'ran', 'the', 'walk', 'walked']

/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function get_feature_names is deprecated; get_feature_names is deprecated in 1.0 and will be removed in 1.2. Please use get_feature_names_out instead.
  warnings.warn(msg, category=FutureWarning)

Améliorer les représentations BoW

Les arguments du vectorizer vont nous permettre d'agir facilement sur la façon dont les données sont représentées. On peut donc chercher à améliorer nos représentations Bag-of-words:

Ne pas prendre en compte les mots trop fréquents:

On peut utiliser l'option max_df=1.0 pour modifier la quantité de mots pris en compte.

Essayer différentes granularités:

Plutôt que de simplement compter les mots, on peut compter les séquences de mots - de taille limitée, bien sur. On appelle une séquence de $n$ mots un $n$-gram: essayons d'utiliser les 2 et 3-grams (bi- et trigrams). On peut aussi tenter d'utiliser les séquences de caractères à la place de séquences de mots.

On s'intéressera aux options analyzer='word' et ngram_range=(1, 2) que l'on changera pour modifier la granularité.

Encore une fois: avoir recours à ces features aura probablement plus d'impact si la quantité de données d'entraînement à notre disposition est limitée !

Pour accélérer les expériences, utilisez l'outil Pipeline de scikit-learn.

from sklearn.pipeline import Pipeline

On fait varier les paramètres suivants :

• max_df = [0, 0.2, 0.5, 0.7, 0.9, 1]
• ngram_range = [(1,1), (1,2), (1,3),(2,2), (2,3), (3,3)]
• analyzer = ["word", "char", "char_wb"]

Le paramètre max_features reste fixé à 10 000

# Create a pipeline for each configuration
models = []

max_df = [0.2, 0.5, 0.7, 0.9]
ngram_range = [(1,1), (1,2), (1,3),(2,2), (2,3), (3,3)]
analyzer = ["word", "char", "char_wb"]

f1_score_list = list()

for i in analyzer:
  models_max_df = []
  for j in max_df:
    print(j)
    models_ngram = []
    for k in ngram_range:
      print(k)
      pipe = Pipeline([
                    ('vec', CountVectorizer(max_features=10000, analyzer=i, max_df=j, ngram_range=k)),
                    ('clf', MultinomialNB())
                    ])
      pipe.fit(train_texts_splt, train_labels_splt)
      models_ngram.append(pipe)

    models_max_df.append(models_ngram)
  models.append(models_max_df)

for n, i in enumerate(analyzer):
  for m, j in enumerate(max_df):
    for o, k in enumerate(ngram_range):
      print('Pipe with {analyzer=' + i + ", max_df=" + str(j) + ", ngram_range=" + str(k) + "}")
      preds = models[n][m][o].predict(val_texts)

      print("---- Classification report ----")
      report_classification = classification_report(val_labels, preds, target_names=["positif", "negatif"], output_dict=True)
      print(classification_report(val_labels, preds, target_names=["positif", "negatif"]))

      f1_score = report_classification['macro avg']['f1-score']
      f1_score_list.append(f1_score)

      cm = confusion_matrix(val_labels, preds)
      cm_disp = ConfusionMatrixDisplay(cm, display_labels=["positif", "negatif"])

      cm_disp.plot()
      plt.show() 
      print("\n\n----------------------------------------------------\n\n")

print("F1-Score")
print(f1_score_list)

0.2
(1, 1)
(1, 2)
(1, 3)
(2, 2)
(2, 3)
(3, 3)
0.5
(1, 1)
(1, 2)
(1, 3)
(2, 2)
(2, 3)
(3, 3)
0.7
(1, 1)
(1, 2)
(1, 3)
(2, 2)
(2, 3)
(3, 3)
0.9
(1, 1)
(1, 2)
(1, 3)
(2, 2)
(2, 3)
(3, 3)
0.2
(1, 1)
(1, 2)
(1, 3)
(2, 2)
(2, 3)
(3, 3)
0.5
(1, 1)
(1, 2)
(1, 3)
(2, 2)
(2, 3)
(3, 3)
0.7
(1, 1)
(1, 2)
(1, 3)
(2, 2)
(2, 3)
(3, 3)
0.9
(1, 1)
(1, 2)
(1, 3)
(2, 2)
(2, 3)
(3, 3)
0.2
(1, 1)
(1, 2)
(1, 3)
(2, 2)
(2, 3)
(3, 3)
0.5
(1, 1)
(1, 2)
(1, 3)
(2, 2)
(2, 3)
(3, 3)
0.7
(1, 1)
(1, 2)
(1, 3)
(2, 2)
(2, 3)
(3, 3)
0.9
(1, 1)
(1, 2)
(1, 3)
(2, 2)
(2, 3)
(3, 3)
Pipe with {analyzer=word, max_df=0.2, ngram_range=(1, 1)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.83      0.87      0.85      1250
     negatif       0.86      0.82      0.84      1250

    accuracy                           0.85      2500
   macro avg       0.85      0.85      0.85      2500
weighted avg       0.85      0.85      0.85      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.2, ngram_range=(1, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.87      0.86      0.87      1250
     negatif       0.86      0.87      0.87      1250

    accuracy                           0.87      2500
   macro avg       0.87      0.87      0.87      2500
weighted avg       0.87      0.87      0.87      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.2, ngram_range=(1, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.87      0.85      0.86      1250
     negatif       0.86      0.88      0.87      1250

    accuracy                           0.86      2500
   macro avg       0.86      0.86      0.86      2500
weighted avg       0.86      0.86      0.86      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.2, ngram_range=(2, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.86      0.83      0.84      1250
     negatif       0.84      0.86      0.85      1250

    accuracy                           0.85      2500
   macro avg       0.85      0.85      0.85      2500
weighted avg       0.85      0.85      0.85      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.2, ngram_range=(2, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.86      0.82      0.84      1250
     negatif       0.83      0.86      0.84      1250

    accuracy                           0.84      2500
   macro avg       0.84      0.84      0.84      2500
weighted avg       0.84      0.84      0.84      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.2, ngram_range=(3, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.80      0.79      0.79      1250
     negatif       0.79      0.80      0.80      1250

    accuracy                           0.79      2500
   macro avg       0.79      0.79      0.79      2500
weighted avg       0.79      0.79      0.79      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.5, ngram_range=(1, 1)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.82      0.87      0.85      1250
     negatif       0.87      0.81      0.84      1250

    accuracy                           0.84      2500
   macro avg       0.84      0.84      0.84      2500
weighted avg       0.84      0.84      0.84      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.5, ngram_range=(1, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.86      0.86      0.86      1250
     negatif       0.86      0.86      0.86      1250

    accuracy                           0.86      2500
   macro avg       0.86      0.86      0.86      2500
weighted avg       0.86      0.86      0.86      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.5, ngram_range=(1, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.86      0.85      0.86      1250
     negatif       0.85      0.86      0.86      1250

    accuracy                           0.86      2500
   macro avg       0.86      0.86      0.86      2500
weighted avg       0.86      0.86      0.86      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.5, ngram_range=(2, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.85      0.83      0.84      1250
     negatif       0.84      0.86      0.85      1250

    accuracy                           0.84      2500
   macro avg       0.85      0.84      0.84      2500
weighted avg       0.85      0.84      0.84      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.5, ngram_range=(2, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.85      0.82      0.84      1250
     negatif       0.83      0.86      0.84      1250

    accuracy                           0.84      2500
   macro avg       0.84      0.84      0.84      2500
weighted avg       0.84      0.84      0.84      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.5, ngram_range=(3, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.80      0.78      0.79      1250
     negatif       0.79      0.80      0.80      1250

    accuracy                           0.79      2500
   macro avg       0.79      0.79      0.79      2500
weighted avg       0.79      0.79      0.79      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.7, ngram_range=(1, 1)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.81      0.87      0.84      1250
     negatif       0.86      0.80      0.83      1250

    accuracy                           0.84      2500
   macro avg       0.84      0.84      0.83      2500
weighted avg       0.84      0.84      0.83      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.7, ngram_range=(1, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.85      0.86      0.85      1250
     negatif       0.86      0.85      0.85      1250

    accuracy                           0.85      2500
   macro avg       0.85      0.85      0.85      2500
weighted avg       0.85      0.85      0.85      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.7, ngram_range=(1, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.86      0.85      0.85      1250
     negatif       0.85      0.86      0.86      1250

    accuracy                           0.85      2500
   macro avg       0.85      0.85      0.85      2500
weighted avg       0.85      0.85      0.85      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.7, ngram_range=(2, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.85      0.83      0.84      1250
     negatif       0.84      0.86      0.85      1250

    accuracy                           0.85      2500
   macro avg       0.85      0.85      0.85      2500
weighted avg       0.85      0.85      0.85      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.7, ngram_range=(2, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.85      0.82      0.84      1250
     negatif       0.83      0.86      0.84      1250

    accuracy                           0.84      2500
   macro avg       0.84      0.84      0.84      2500
weighted avg       0.84      0.84      0.84      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.7, ngram_range=(3, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.80      0.78      0.79      1250
     negatif       0.79      0.80      0.80      1250

    accuracy                           0.79      2500
   macro avg       0.79      0.79      0.79      2500
weighted avg       0.79      0.79      0.79      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.9, ngram_range=(1, 1)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.81      0.87      0.84      1250
     negatif       0.86      0.79      0.83      1250

    accuracy                           0.83      2500
   macro avg       0.83      0.83      0.83      2500
weighted avg       0.83      0.83      0.83      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.9, ngram_range=(1, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.85      0.86      0.85      1250
     negatif       0.85      0.85      0.85      1250

    accuracy                           0.85      2500
   macro avg       0.85      0.85      0.85      2500
weighted avg       0.85      0.85      0.85      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.9, ngram_range=(1, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.85      0.85      0.85      1250
     negatif       0.85      0.86      0.85      1250

    accuracy                           0.85      2500
   macro avg       0.85      0.85      0.85      2500
weighted avg       0.85      0.85      0.85      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.9, ngram_range=(2, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.85      0.83      0.84      1250
     negatif       0.84      0.86      0.85      1250

    accuracy                           0.85      2500
   macro avg       0.85      0.85      0.85      2500
weighted avg       0.85      0.85      0.85      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.9, ngram_range=(2, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.85      0.82      0.84      1250
     negatif       0.83      0.86      0.84      1250

    accuracy                           0.84      2500
   macro avg       0.84      0.84      0.84      2500
weighted avg       0.84      0.84      0.84      2500

----------------------------------------------------


Pipe with {analyzer=word, max_df=0.9, ngram_range=(3, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.80      0.78      0.79      1250
     negatif       0.79      0.80      0.80      1250

    accuracy                           0.79      2500
   macro avg       0.79      0.79      0.79      2500
weighted avg       0.79      0.79      0.79      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.2, ngram_range=(1, 1)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.54      0.75      0.63      1250
     negatif       0.59      0.36      0.45      1250

    accuracy                           0.56      2500
   macro avg       0.57      0.56      0.54      2500
weighted avg       0.57      0.56      0.54      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.2, ngram_range=(1, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.69      0.69      0.69      1250
     negatif       0.69      0.68      0.69      1250

    accuracy                           0.69      2500
   macro avg       0.69      0.69      0.69      2500
weighted avg       0.69      0.69      0.69      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.2, ngram_range=(1, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.79      0.81      0.80      1250
     negatif       0.81      0.78      0.79      1250

    accuracy                           0.80      2500
   macro avg       0.80      0.80      0.80      2500
weighted avg       0.80      0.80      0.80      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.2, ngram_range=(2, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.69      0.68      0.69      1250
     negatif       0.69      0.70      0.69      1250

    accuracy                           0.69      2500
   macro avg       0.69      0.69      0.69      2500
weighted avg       0.69      0.69      0.69      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.2, ngram_range=(2, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.78      0.81      0.80      1250
     negatif       0.80      0.78      0.79      1250

    accuracy                           0.79      2500
   macro avg       0.79      0.79      0.79      2500
weighted avg       0.79      0.79      0.79      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.2, ngram_range=(3, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.79      0.82      0.80      1250
     negatif       0.81      0.78      0.80      1250

    accuracy                           0.80      2500
   macro avg       0.80      0.80      0.80      2500
weighted avg       0.80      0.80      0.80      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.5, ngram_range=(1, 1)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.58      0.57      0.57      1250
     negatif       0.58      0.59      0.58      1250

    accuracy                           0.58      2500
   macro avg       0.58      0.58      0.58      2500
weighted avg       0.58      0.58      0.58      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.5, ngram_range=(1, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.71      0.70      0.71      1250
     negatif       0.70      0.72      0.71      1250

    accuracy                           0.71      2500
   macro avg       0.71      0.71      0.71      2500
weighted avg       0.71      0.71      0.71      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.5, ngram_range=(1, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.78      0.81      0.79      1250
     negatif       0.80      0.77      0.78      1250

    accuracy                           0.79      2500
   macro avg       0.79      0.79      0.79      2500
weighted avg       0.79      0.79      0.79      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.5, ngram_range=(2, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.72      0.72      0.72      1250
     negatif       0.72      0.71      0.72      1250

    accuracy                           0.72      2500
   macro avg       0.72      0.72      0.72      2500
weighted avg       0.72      0.72      0.72      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.5, ngram_range=(2, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.78      0.81      0.79      1250
     negatif       0.80      0.77      0.78      1250

    accuracy                           0.79      2500
   macro avg       0.79      0.79      0.79      2500
weighted avg       0.79      0.79      0.79      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.5, ngram_range=(3, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.78      0.82      0.80      1250
     negatif       0.81      0.77      0.79      1250

    accuracy                           0.80      2500
   macro avg       0.80      0.80      0.80      2500
weighted avg       0.80      0.80      0.80      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.7, ngram_range=(1, 1)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.58      0.56      0.57      1250
     negatif       0.58      0.59      0.59      1250

    accuracy                           0.58      2500
   macro avg       0.58      0.58      0.58      2500
weighted avg       0.58      0.58      0.58      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.7, ngram_range=(1, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.70      0.70      0.70      1250
     negatif       0.70      0.70      0.70      1250

    accuracy                           0.70      2500
   macro avg       0.70      0.70      0.70      2500
weighted avg       0.70      0.70      0.70      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.7, ngram_range=(1, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.75      0.80      0.78      1250
     negatif       0.79      0.74      0.76      1250

    accuracy                           0.77      2500
   macro avg       0.77      0.77      0.77      2500
weighted avg       0.77      0.77      0.77      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.7, ngram_range=(2, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.71      0.72      0.71      1250
     negatif       0.72      0.70      0.71      1250

    accuracy                           0.71      2500
   macro avg       0.71      0.71      0.71      2500
weighted avg       0.71      0.71      0.71      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.7, ngram_range=(2, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.75      0.80      0.78      1250
     negatif       0.79      0.74      0.76      1250

    accuracy                           0.77      2500
   macro avg       0.77      0.77      0.77      2500
weighted avg       0.77      0.77      0.77      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.7, ngram_range=(3, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.76      0.82      0.79      1250
     negatif       0.80      0.74      0.77      1250

    accuracy                           0.78      2500
   macro avg       0.78      0.78      0.78      2500
weighted avg       0.78      0.78      0.78      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.9, ngram_range=(1, 1)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.58      0.56      0.57      1250
     negatif       0.57      0.58      0.58      1250

    accuracy                           0.57      2500
   macro avg       0.57      0.57      0.57      2500
weighted avg       0.57      0.57      0.57      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.9, ngram_range=(1, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.69      0.71      0.70      1250
     negatif       0.70      0.68      0.69      1250

    accuracy                           0.70      2500
   macro avg       0.70      0.70      0.70      2500
weighted avg       0.70      0.70      0.70      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.9, ngram_range=(1, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.73      0.80      0.76      1250
     negatif       0.78      0.71      0.74      1250

    accuracy                           0.75      2500
   macro avg       0.76      0.75      0.75      2500
weighted avg       0.76      0.75      0.75      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.9, ngram_range=(2, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.69      0.72      0.71      1250
     negatif       0.71      0.67      0.69      1250

    accuracy                           0.70      2500
   macro avg       0.70      0.70      0.70      2500
weighted avg       0.70      0.70      0.70      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.9, ngram_range=(2, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.74      0.80      0.77      1250
     negatif       0.78      0.72      0.75      1250

    accuracy                           0.76      2500
   macro avg       0.76      0.76      0.76      2500
weighted avg       0.76      0.76      0.76      2500

----------------------------------------------------


Pipe with {analyzer=char, max_df=0.9, ngram_range=(3, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.74      0.81      0.77      1250
     negatif       0.79      0.72      0.75      1250

    accuracy                           0.76      2500
   macro avg       0.77      0.76      0.76      2500
weighted avg       0.77      0.76      0.76      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.2, ngram_range=(1, 1)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.54      0.75      0.63      1250
     negatif       0.59      0.36      0.45      1250

    accuracy                           0.56      2500
   macro avg       0.57      0.56      0.54      2500
weighted avg       0.57      0.56      0.54      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.2, ngram_range=(1, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.69      0.69      0.69      1250
     negatif       0.69      0.69      0.69      1250

    accuracy                           0.69      2500
   macro avg       0.69      0.69      0.69      2500
weighted avg       0.69      0.69      0.69      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.2, ngram_range=(1, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.78      0.81      0.80      1250
     negatif       0.81      0.78      0.79      1250

    accuracy                           0.79      2500
   macro avg       0.79      0.79      0.79      2500
weighted avg       0.79      0.79      0.79      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.2, ngram_range=(2, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.69      0.68      0.69      1250
     negatif       0.69      0.70      0.69      1250

    accuracy                           0.69      2500
   macro avg       0.69      0.69      0.69      2500
weighted avg       0.69      0.69      0.69      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.2, ngram_range=(2, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.78      0.81      0.80      1250
     negatif       0.80      0.77      0.79      1250

    accuracy                           0.79      2500
   macro avg       0.79      0.79      0.79      2500
weighted avg       0.79      0.79      0.79      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.2, ngram_range=(3, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.79      0.82      0.80      1250
     negatif       0.81      0.78      0.79      1250

    accuracy                           0.80      2500
   macro avg       0.80      0.80      0.80      2500
weighted avg       0.80      0.80      0.80      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.5, ngram_range=(1, 1)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.58      0.57      0.57      1250
     negatif       0.58      0.59      0.58      1250

    accuracy                           0.58      2500
   macro avg       0.58      0.58      0.58      2500
weighted avg       0.58      0.58      0.58      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.5, ngram_range=(1, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.71      0.70      0.71      1250
     negatif       0.70      0.72      0.71      1250

    accuracy                           0.71      2500
   macro avg       0.71      0.71      0.71      2500
weighted avg       0.71      0.71      0.71      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.5, ngram_range=(1, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.77      0.81      0.79      1250
     negatif       0.80      0.76      0.78      1250

    accuracy                           0.79      2500
   macro avg       0.79      0.79      0.79      2500
weighted avg       0.79      0.79      0.79      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.5, ngram_range=(2, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.71      0.72      0.72      1250
     negatif       0.72      0.71      0.71      1250

    accuracy                           0.72      2500
   macro avg       0.72      0.72      0.72      2500
weighted avg       0.72      0.72      0.72      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.5, ngram_range=(2, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.77      0.82      0.79      1250
     negatif       0.80      0.76      0.78      1250

    accuracy                           0.79      2500
   macro avg       0.79      0.79      0.79      2500
weighted avg       0.79      0.79      0.79      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.5, ngram_range=(3, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.78      0.82      0.80      1250
     negatif       0.81      0.77      0.79      1250

    accuracy                           0.80      2500
   macro avg       0.80      0.80      0.80      2500
weighted avg       0.80      0.80      0.80      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.7, ngram_range=(1, 1)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.58      0.56      0.57      1250
     negatif       0.58      0.59      0.59      1250

    accuracy                           0.58      2500
   macro avg       0.58      0.58      0.58      2500
weighted avg       0.58      0.58      0.58      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.7, ngram_range=(1, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.70      0.70      0.70      1250
     negatif       0.70      0.70      0.70      1250

    accuracy                           0.70      2500
   macro avg       0.70      0.70      0.70      2500
weighted avg       0.70      0.70      0.70      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.7, ngram_range=(1, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.76      0.80      0.78      1250
     negatif       0.79      0.74      0.76      1250

    accuracy                           0.77      2500
   macro avg       0.77      0.77      0.77      2500
weighted avg       0.77      0.77      0.77      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.7, ngram_range=(2, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.71      0.72      0.71      1250
     negatif       0.72      0.70      0.71      1250

    accuracy                           0.71      2500
   macro avg       0.71      0.71      0.71      2500
weighted avg       0.71      0.71      0.71      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.7, ngram_range=(2, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.75      0.80      0.78      1250
     negatif       0.79      0.74      0.76      1250

    accuracy                           0.77      2500
   macro avg       0.77      0.77      0.77      2500
weighted avg       0.77      0.77      0.77      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.7, ngram_range=(3, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.76      0.82      0.79      1250
     negatif       0.81      0.75      0.77      1250

    accuracy                           0.78      2500
   macro avg       0.78      0.78      0.78      2500
weighted avg       0.78      0.78      0.78      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.9, ngram_range=(1, 1)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.58      0.56      0.57      1250
     negatif       0.57      0.58      0.58      1250

    accuracy                           0.57      2500
   macro avg       0.57      0.57      0.57      2500
weighted avg       0.57      0.57      0.57      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.9, ngram_range=(1, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.69      0.71      0.70      1250
     negatif       0.70      0.68      0.69      1250

    accuracy                           0.70      2500
   macro avg       0.70      0.70      0.70      2500
weighted avg       0.70      0.70      0.70      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.9, ngram_range=(1, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.74      0.80      0.77      1250
     negatif       0.78      0.72      0.75      1250

    accuracy                           0.76      2500
   macro avg       0.76      0.76      0.76      2500
weighted avg       0.76      0.76      0.76      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.9, ngram_range=(2, 2)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.69      0.72      0.71      1250
     negatif       0.71      0.68      0.69      1250

    accuracy                           0.70      2500
   macro avg       0.70      0.70      0.70      2500
weighted avg       0.70      0.70      0.70      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.9, ngram_range=(2, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.74      0.80      0.77      1250
     negatif       0.78      0.72      0.75      1250

    accuracy                           0.76      2500
   macro avg       0.76      0.76      0.76      2500
weighted avg       0.76      0.76      0.76      2500

----------------------------------------------------


Pipe with {analyzer=char_wb, max_df=0.9, ngram_range=(3, 3)}
---- Classification report ----
              precision    recall  f1-score   support

     positif       0.75      0.81      0.78      1250
     negatif       0.80      0.73      0.76      1250

    accuracy                           0.77      2500
   macro avg       0.77      0.77      0.77      2500
weighted avg       0.77      0.77      0.77      2500

----------------------------------------------------


F1-Score
[0.8463054717173251, 0.8655996559351191, 0.8647853751861803, 0.8471646889297303, 0.8415314401622719, 0.7947881469633686, 0.8422464363710209, 0.8587997966717072, 0.8587949166169981, 0.844774567865199, 0.8395332201448955, 0.7935776733611507, 0.8349463719930594, 0.8543991613391694, 0.8547994191976769, 0.8455746989586774, 0.8395278774092227, 0.7935776733611507, 0.8321576356258438, 0.8519976319621114, 0.8527991521231162, 0.8455746989586774, 0.8395278774092227, 0.7935776733611507, 0.5393476830891503, 0.685998743994976, 0.7959424067848909, 0.6911873510338983, 0.7931443641081706, 0.7991377809190174, 0.5767609942932341, 0.7091552797158092, 0.7867112377487016, 0.7155995904634104, 0.7886862624939247, 0.7958662188852086, 0.5791027559007232, 0.7003988015952065, 0.7685386894388289, 0.7115796490600377, 0.7697211230688813, 0.7768778115598924, 0.5735538755871835, 0.6975146265281913, 0.7535652891700961, 0.6994091127629689, 0.7579648789407645, 0.7643764053264397, 0.5401784356895305, 0.6883999501439919, 0.7943303684895557, 0.6915821857870511, 0.7919167667066827, 0.798305897599584, 0.5767609942932341, 0.7087580611608072, 0.7870604479351588, 0.7151983595425508, 0.7886526993853635, 0.7954441775566956, 0.5791027559007232, 0.7011976573896339, 0.7709770599091981, 0.7123833872644484, 0.7705709012791813, 0.7829060026249948, 0.5735538755871835, 0.697118537001712, 0.7564408574307331, 0.6994210473147293, 0.7604011541772897, 0.7711963904327234]

import pandas as pd
max_df = [0.2, 0.5, 0.7, 0.9]
ngram_range = [(1,1), (1,2), (1,3),(2,2), (2,3), (3,3)]
analyzer = ["word", "char", "char_wb"]

result_df = pd.DataFrame(columns=['analyzer', 'max_df','ngram_range'])

for i in analyzer:
  for j in max_df:
    for k in ngram_range:
      new_row = {'analyzer':i, 'max_df':j, 'ngram_range':str(k)}
      result_df = result_df.append(new_row, ignore_index=True)

result_df.insert (0, "f1-score", f1_score_list)

result_df

	f1-score	analyzer	max_df	ngram_range
0	0.846305	word	0.2	(1, 1)
1	0.865600	word	0.2	(1, 2)
2	0.864785	word	0.2	(1, 3)
3	0.847165	word	0.2	(2, 2)
4	0.841531	word	0.2	(2, 3)
...	...	...	...	...
67	0.697119	char_wb	0.9	(1, 2)
68	0.756441	char_wb	0.9	(1, 3)
69	0.699421	char_wb	0.9	(2, 2)
70	0.760401	char_wb	0.9	(2, 3)
71	0.771196	char_wb	0.9	(3, 3)

72 rows × 4 columns

#!pip install -U hiplot

import hiplot as hip
result_hiplot = hip.Experiment.from_dataframe(result_df)
result_hiplot.display()

Loading HiPlot...

<hiplot.ipython.IPythonExperimentDisplayed at 0x7f5e1eb71bd0>

Output HiPlot

Pour éviter d'avoir installer HiPlot j'ai intégrer des captures d'écran du graphe généré par HiPlot

Output HiPlot

La combinaison des meilleures hyperparamètres

Pour connaitre l'impact des différents paramètre de CountVectorzier(), j'ai utilisé l'outil HiPlot (développé par Facebook). On peut facilement observer que l'ensemble des paramètres qui donne le meilleur f1-score sont:

• analyzer = word
• max_df = 0.2
• ngram_range = (1,3)

Tf-idf:

Il s'agit du produit de la fréquence du terme (TF) et de sa fréquence inverse dans les documents (IDF). Cette méthode est habituellement utilisée pour extraire l'importance d'un terme $i$ dans un document $j$ relativement au reste du corpus, à partir d'une matrice d'occurences $mots \times documents$. Ainsi, pour une matrice $\mathbf{T}$ de $|V|$ termes et $D$ documents: $$\text{TF}(T, w, d) = \frac{T_{w,d}}{\sum_{w'=1}^{|V|} T_{w',d}} $$

$$\text{IDF}(T, w) = \log\left(\frac{D}{|\{d : T_{w,d} > 0\}|}\right)$$$$\text{TF-IDF}(T, w, d) = \text{TF}(X, w, d) \cdot \text{IDF}(T, w)$$

On peut l'adapter à notre cas en considérant que le contexte du deuxième mot est le document. Cependant, TF-IDF est généralement plus adaptée aux matrices peu denses, puisque cette mesure pénalisera les termes qui apparaissent dans une grande partie des documents.

from sklearn.feature_extraction.text import TfidfTransformer

# You can use Pipeline here too
pipe = Pipeline([('vec_count', CountVectorizer(max_features= 10000, analyzer='word', max_df=0.2, ngram_range=(1,3))), 
                 ('tfidf', TfidfTransformer()),
                 ('clf', MultinomialNB())
                 ])

pipe.fit(train_texts_splt, train_labels_splt)

print("features names")
feat_names = pipe['vec_count'].get_feature_names()

print("\n-------------------------\n")

print("Vocabulary")
vocab = pipe['vec_count'].vocabulary_
print(vocab)

print("\n-------------------------\n")

print("CountVectorizer")
vec_count = pipe['vec_count'].transform(train_texts_splt).toarray()
print(vec_count)

print("\n-------------------------\n")

print("TF-IDF")
tf_idf = pipe['tfidf'].idf_
print(tf_idf)
print(len(tf_idf))

print("\n-------------------------\n")

# Make predictions
predictions = pipe.predict(val_texts)

print("Predictions")
print(predictions)

# Show the results in a readable format
print("\n\n---- Classification report ----")

report_classification = classification_report(val_labels, predictions, target_names=["positif", "negatif"], output_dict=True)

print(classification_report(val_labels, predictions, target_names=["positif", "negatif"]))

cm = confusion_matrix(val_labels, predictions)
cm_disp = ConfusionMatrixDisplay(cm, display_labels=["positif", "negatif"])

cm_disp.plot()
plt.show()

features names

-------------------------

Vocabulary
{'bought': 1187, 'blockbuster': 1145, 'guy': 3338, 'behind': 1054, 'said': 6695, 'reason': 6484, 'cheap': 1690, 'disc': 2196, 'failed': 2654, 'mention': 5099, 'poor': 6242, 'effort': 2393, 'sucked': 7421, 'harder': 3400, 'paris': 6058, 'hotel': 3740, 'room': 6662, 'home': 3708, 'video': 9245, 'talking': 7511, 'videos': 9248, 'since': 7050, 'fair': 2660, 'game': 3124, 'release': 6529, 'films': 2844, 'mean': 5062, 'say': 6730, 'used': 9179, 'actors': 131, 'your': 9985, 'friends': 3065, 'lame': 4626, 'ideas': 3798, 'together': 8931, 'weekend': 9500, 'production': 6334, '00': 0, 'budget': 1387, 'someone': 7167, 'fall': 2667, 'down': 2297, 'soundtrack': 7201, 'slap': 7080, 'take': 7491, 'lonely': 4823, 'desperation': 2110, 'here': 3591, 'fast': 2706, 'through': 8626, 'side': 7028, 'ready': 6457, 'until': 9138, 'next': 5460, 'night': 5468, 'while': 9620, 'watching': 9441, 'day': 2032, 'horror': 3729, '99': 54, 'keep': 4550, 'different': 2164, 'now': 5581, 'grim': 3310, 'look': 4829, 'back': 898, 'catch': 1617, 'moments': 5174, 'listed': 4785, 'wonderful': 9791, 'imdb': 3848, 'viewers': 9254, 'hilarious': 3627, 'sure': 7455, 'enough': 2465, 'once': 5846, 'got': 3268, 'over': 6014, 'pain': 6044, 'utter': 9188, 'enjoy': 2454, 'downright': 2303, 'funny': 3108, 'stuff': 7390, 'lot': 4859, 'check': 1691, 'flick': 2912, 'hell': 3558, 'might': 5121, 'worth': 9838, 'crap': 1947, 'the guy': 7932, 'behind the': 1055, 'said the': 6698, 'the reason': 8137, 'was so': 9384, 'was because': 9340, 'because the': 1014, 'failed to': 2655, 'to mention': 8823, 'mention that': 5100, 'that the': 7680, 'film was': 2830, 'has it': 3418, 'it been': 4298, 'them as': 8321, 'to say': 8857, 'used to': 9181, 'actors and': 132, 'and so': 496, 'so on': 7120, 'any more': 604, 'friends and': 3066, 'the production': 8129, 'with an': 9723, 'budget and': 1388, 'and get': 412, 'to fall': 8764, 'down the': 2300, 'the soundtrack': 8193, 'it on': 4381, 'for some': 2977, 'me to': 5056, 'to take': 8884, 'but here': 1425, 'here the': 3604, 'most of': 5215, 'of this': 5743, 'this and': 8466, 'it to': 4416, 'to one': 8833, 'until the': 9139, 'the next': 8065, 'while watching': 9627, 'home and': 3709, 'film made': 2811, 'look like': 4834, 'like the': 4751, 'back on': 905, 'on to': 5837, 'to catch': 8732, 'up on': 9155, 'on some': 5826, 'some of': 7151, 'the wonderful': 8286, 'over the': 6020, 'the horror': 7949, 'down to': 2301, 'and there': 527, 'there lot': 8369, 'lot of': 4862, 'of it': 5657, 'it might': 4372, 'worth it': 9839, 'it was so': 4433, 'the film was': 7893, 'and so on': 497, 'it on the': 4382, 'some of the': 7153, 'down to the': 2302, 'devil': 2128, 'hunter': 3785, 'known': 4603, 'amongst': 319, 'english': 2453, 'speaking': 7211, 'audiences': 869, 'starts': 7281, 'actress': 137, 'model': 5168, 'laura': 4654, 'checking': 1695, 'locations': 4819, 'new': 5455, 'along': 287, 'assistant': 804, 'jane': 4465, 'long': 4824, 'days': 2035, 'work': 9802, 'two': 9070, 'character': 1653, 'named': 5398, 'chris': 1716, 'thomas': 8586, 'having': 3490, 'helped': 3563, 'agent': 206, 'gets': 3166, 'rent': 6557, 'hero': 3607, 'peter': 6146, 'al': 219, 'situation': 7070, 'island': 4271, 'million': 5134, 'told': 8936, 'paid': 6043, '000': 1, 'further': 3117, '10': 2, 'brings': 1367, 'faster': 2709, 'rat': 6427, 'vietnam': 9249, 'buddy': 1386, 'pilot': 6174, 'jack': 4458, 'save': 6718, 'neither': 5441, 'want': 9301, 'hand': 3370, 'things': 8440, 'particular': 6070, 've': 9201, 'lived': 4802, 'managed': 4983, 'build': 1390, 'monster': 5184, 'dude': 2342, 'burt': 1401, 'altman': 302, 'eyes': 2631, 'god': 3217, 'human': 3773, 'young': 9978, 'white': 9629, 'female': 2747, 'flesh': 2911, 'spanish': 7208, 'french': 3058, 'german': 3149, 'co': 1765, 'written': 9882, 'directed': 2177, 'jesus': 4481, 'credit': 1963, 'music': 5358, 'certain': 1633, 'amount': 320, 'uk': 9084, 'placed': 6182, 'list': 4783, 'early': 2364, '80': 50, 'under': 9096, 'title': 8689, 'therefore': 8383, 'banned': 940, 'idea': 3793, 'why': 9670, 'isn': 4272, 'afraid': 176, 'associated': 805, 'turkey': 9044, 'decides': 2064, 'wants': 9311, 'hide': 3615, 'brown': 1381, 'imagine': 3846, 'die': 2159, 'hard': 3396, 'fan': 2684, 'thing': 8431, 'script': 6803, 'sorry': 7190, 'obviously': 5604, 'another': 593, 'less': 4699, 'impressed': 3856, 'finished': 2877, 'product': 6333, 'wanted': 9306, 'awful': 893, 'simple': 7046, 'straight': 7357, 'forward': 3031, 'start': 7273, 'boring': 1174, 'ever': 2541, 'without': 9767, 'slightest': 7087, 'bit': 1127, 'tension': 7559, 'excitement': 2586, 'involved': 4081, 'big': 1113, 'black': 1135, 'stupid': 7394, 'looking': 4838, 'plus': 6223, 'tame': 7516, 'scenes': 6768, 'fails': 2657, 'action': 119, 'adventure': 168, 'success': 7413, 'avoid': 879, 'director': 2184, 'shows': 7021, 'usual': 9186, 'throughout': 8632, 'head': 3537, 'achieved': 105, 'actor': 126, 'lying': 4908, 'ground': 3315, 'large': 4631, 'leaves': 4680, 'around': 710, 'bottom': 1184, 'neck': 5423, 'try': 9034, 'give': 3182, 'impression': 3858, 'attached': 849, 'anything': 617, 'endless': 2445, 'walking': 9293, 'jungle': 4515, 'getting': 3169, 'doing': 2252, 'either': 2397, 'becomes': 1022, 'incredibly': 4003, 'dull': 2347, 'tedious': 7535, 'minutes': 5147, 'forget': 3017, 'goes': 3219, 'state': 7286, 'must': 5365, 'scene': 6752, 'supposed': 7451, 'turning': 9051, 'camera': 1530, 'floor': 2915, 'never': 5445, 'onto': 5906, 'pulls': 6372, 'himself': 3646, 'gore': 3264, 'far': 2693, 'go': 3204, 'gross': 3314, 'close': 1753, 'ups': 9167, 'mouth': 5229, 'bits': 1132, 'meat': 5072, 'man': 4972, 'blood': 1148, 'handful': 3372, 'nudity': 5591, 'unpleasant': 9135, 'rape': 6423, 'low': 4894, 'poorly': 6243, 'special': 7213, 'effects': 2389, 'rock': 6644, 'values': 9194, 'decent': 2059, 'setting': 6927, 'least': 4673, 'looks': 4843, 'authentic': 874, 'sucks': 7422, 'sound': 7197, 'become': 1020, 'annoying': 591, 'lots': 4867, 'heavy': 3554, 'whenever': 9594, 'screen': 6797, 'whole': 9662, 'dubbed': 2340, 'anyway': 623, 'act': 110, 'terrible': 7563, 'fatal': 2711, 'mistake': 5161, 'sleazy': 7083, 'atmosphere': 845, 'those': 8588, 'pretty': 6297, 'anyone': 614, 'cinematic': 1726, 'experience': 2605, 'should': 6996, 'wide': 9681, 'possible': 6261, 'as it': 750, 'it more': 4374, 'starts with': 7285, 'for her': 2958, 'along with': 290, 'with her': 9731, 'of her': 5647, 'by the': 1506, 'to rent': 8853, 'who is': 9644, 'the situation': 8184, 'on an': 5801, 'is told': 4251, 'that he': 7630, 'he will': 3535, 'will be': 9687, 'to get': 8776, 'if he': 3806, 'as well': 785, 'are on': 680, 'the island': 7963, 'on how': 5816, 'how to': 3762, 'to save': 8855, 'so the': 7123, 'has the': 3429, 'want to': 9302, 'that much': 7660, 'just to': 4540, 'this particular': 8555, 'in all': 3864, 'all the': 256, 'they ve': 8424, 'managed to': 4984, 'to build': 8726, 'now that': 5585, 'br this': 1323, 'directed by': 2178, 'who also': 9631, 'gets the': 3167, 'credit for': 1964, 'the music': 8054, 'amount of': 321, 'here in': 3600, 'the uk': 8250, 'the video': 8261, 'the early': 7839, 'said that': 6697, 'that have': 7629, 'have no': 3464, 'no idea': 5477, 'is one': 4202, 'bad film': 919, 'film even': 2789, 'associated with': 806, 'he wants': 3532, 'wants to': 9312, 'under the': 9097, 'even the': 2529, 'the most': 8035, 'die hard': 2160, 'would have': 9854, 'this thing': 8571, 'thing the': 8438, 'the script': 8167, 'who was': 9657, 'another one': 595, 'less than': 4700, 'impressed with': 3857, 'is awful': 4111, 'it as': 4291, 'as that': 771, 'that for': 7623, 'film is': 2802, 'is so': 4223, 'plot is': 6215, 've ever': 9204, 'ever seen': 2543, 'without the': 9771, 'the slightest': 8185, 'bit of': 1129, 'side of': 7029, 'of things': 5742, 'as we': 784, 'we get': 9476, 'horror film': 3730, 'as an': 725, 'an action': 323, 'it has': 4337, 'has no': 3423, 'no more': 5482, 'one to': 5886, 'to avoid': 8706, 'his usual': 3684, 'by an': 1495, 'an actor': 324, 'the ground': 7929, 'around the': 713, 'the bottom': 7770, 'bottom of': 1186, 'of his': 5649, 'to try': 8908, 'give the': 3185, 'the impression': 7959, 'it not': 4378, 'scenes are': 6770, 'the action': 7723, 'action is': 121, 'scenes of': 6775, 'of people': 5686, 'to not': 8831, 'not really': 5545, 'when they': 9589, 'they get': 8407, 'it becomes': 4297, 'to watch': 8916, '10 minutes': 6, 'goes on': 3220, 'on for': 5812, 'in it': 3896, 'mention the': 5101, 'is supposed': 4231, 'supposed to': 7452, 'on it': 5819, 'along the': 288, 'the floor': 7907, 'look at': 4831, 'the way': 8270, 'way he': 9455, 'he never': 3520, 'as he': 740, 'he just': 3513, 'the gore': 7925, 'isn that': 4276, 'that great': 7626, 'great as': 3292, 'as far': 733, 'far as': 2694, 'is very': 4258, 'there are': 8350, 'are some': 687, 'close ups': 1756, 'man is': 4976, 'there some': 8374, 'handful of': 3373, 'scene br': 6754, 'must have': 5367, 'have had': 3457, 'low budget': 4895, 'film with': 2836, 'special effects': 7214, 'production values': 6336, 'the only': 8074, 'thing about': 8432, 'about it': 67, 'at least': 825, 'as there': 776, 'there is': 8361, 'lots of': 4868, 'is on': 4200, 'on screen': 5825, 'the acting': 7720, 'the whole': 8277, 'whole thing': 9666, 'but no': 1445, 'no one': 5483, 'one in': 5864, 'can act': 1536, 'is terrible': 4233, 'film that': 2823, 'of being': 5627, 'only good': 5896, 'good things': 3259, 'can say': 1554, 'say is': 6733, 'is that': 4235, 'that it': 7646, 'to it': 8796, 'are pretty': 682, 'looking for': 4840, 'as possible': 763, 'in all the': 3865, 'br br this': 1257, 'in the uk': 3965, 'as it was': 752, 'in the early': 3945, 'have no idea': 3465, 'as it is': 751, 'it is one': 4352, 'he wants to': 3533, 'the film is': 7887, 'is one of': 4203, 'one of the': 5874, 've ever seen': 9205, 'this is one': 8510, 'is supposed to': 4232, 'supposed to be': 7453, 'look at the': 4832, 'the way he': 8271, 'as far as': 734, 'this is very': 8512, 'there are some': 8355, 'scene br br': 6755, 'it is the': 4356, 'the whole thing': 8280, 'the only good': 8075, 'is that it': 4236, 'that it has': 7647, 'shooting': 6981, 'cutting': 2000, 'crew': 1967, 'group': 3316, 'filmmakers': 2843, 'thoughtful': 8611, 'yes': 9905, 'clever': 1746, 'zero': 9996, 'dollar': 2254, 'knowledge': 4602, 'kind': 4578, 'others': 5967, 'feature': 2724, 'these': 8384, 'guys': 3343, 'ones': 5891, 'shorts': 6988, 'collection': 1772, 'horrors': 3734, 'development': 2124, 'working': 9817, 'fun': 3100, 'll': 4810, 'business': 1404, 'harsh': 3405, 'insulting': 4041, 'criticism': 1977, 'wondering': 9793, 'reviewer': 6606, 'heard': 3543, 'word': 9800, 'dialogue': 2134, 'thought': 8602, 'concept': 1847, 'visual': 9271, 'mindless': 5139, 'view': 9250, 'audience': 867, 'let': 4704, 'empty': 2424, 'bring': 1365, 'itself': 4456, 'expect': 2598, 'put': 6382, 'thriller': 8622, 'genre': 3144, 'due': 2343, 'supernatural': 7446, 'premise': 6283, 'drama': 2311, 'depth': 2094, 'beyond': 1110, 'stick': 7313, 'message': 5106, 'doesn': 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actress': 325, 'kind of movie': 4580, 'is the kind': 4242, 'more and': 5195, 'more and more': 5196, 'beast': 996, 'outside the': 6012, 'the beast': 7751, 'movie then': 5296, 'decision': 2066, 'to everyone': 8761, 'the incredible': 7961, 'ethan': 2511, 'they are not': 8396, 'the edge of': 7842, 'from my': 3075, 'dig': 2169, 'the actress': 7728, 'khan': 4561, 'pie': 6166, 'toy': 8979, 'the crew': 7817, 'for long': 2965, 'he been': 3494, 'for long time': 2966, 'bakshi': 933, 'pack': 6040, 'he not': 3521, 'isn it': 4274, 'fashioned': 2705, 'members of the': 5087, 'that at': 7602, 'appeared in': 642, 'like one': 4747, 'it was great': 4427, 'with more': 9740, 'inspiring': 4032, 'catherine': 1620, 'aware of': 884, 'prepared': 6286, 'least it': 4674, 'away the': 889, 'basis': 953, 'and perhaps': 484, 'nudity and': 5592, 'neo': 5443, 'jewish': 4483, 'invisible': 4080, 'pool': 6241, 'it won': 4443, 'old fashioned': 5794, 'video game': 9246, 'ideal': 3797, 'would be the': 9848, 'to which': 8922, 'possibility': 6260, 'to pull': 8846, 'stanwyck': 7262, 'and you ll': 569, 'burned': 1398, 'antwone': 601, 'have seen in': 3472, 'women are': 9782, 'blind': 1143, 'welles': 9525, 'into her': 4066, 'for the role': 2989, 'the so': 8187, 'folk': 2927, 'that about': 7592, 'up br': 9147, 'up br br': 9148, 'think is': 8450, 'sits': 7068, 'the real world': 8135, 'than he': 7576, 'movie making': 5284, 'we never': 9483, 'remember that': 6543, 'homeless': 3710, 'the gang': 7919, 'bird': 1123, 'is must see': 4185, 'narrator': 5403, 'and actually': 353, 'britain': 1368, 'dolls': 2256, 'bathroom': 955, 'dixon': 2210, 'victoria': 9243, 'scary movie': 6750, 'funny br': 3111, 'the narrative': 8061, 'it bad': 4294, 'funny br br': 3112, 'separate': 6899, 'channels': 1650, 'the matrix': 8019, 'the various': 8258, 'it simply': 4405, 'scooby': 6789, 'doo': 2289, 'like me': 4745, 'elvira': 2411, 'experiment': 2608, 'is left': 4173, 'the work': 8290, 'characters but': 1670, 'all the more': 259, 'out of his': 5991, 'bridget': 1358, 'destroying': 2115, 'spielberg': 7226, 'lucas': 4899, 'chaos': 1651, 'has become': 3410, 'reduced': 6508, 'it appears': 4290, 'ollie': 5799, 'smoke': 7100, 'has nothing to': 3426, 'uwe': 9190, 'the zombies': 8307, 'helen': 3557, 'stiller': 7320, 'br br br': 1222, 'attacks': 852, 'all his': 242, 'grayson': 3289, 'to think that': 8901, 'everyone in': 2555, 'ha': 3344, 'you re looking': 9955, 'titled': 8691, 'bullets': 1393, 'has got': 3414, 'lincoln': 4772, 'boll': 1162, 'boy who': 1195, 'bourne': 1189, 'pulling': 6371, 'neil': 5440, 'matthau': 5030, 'to no': 8830, 'blob': 1144, 'europa': 2512, 'rob roy': 6637}

-------------------------

CountVectorizer

/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function get_feature_names is deprecated; get_feature_names is deprecated in 1.0 and will be removed in 1.2. Please use get_feature_names_out instead.
  warnings.warn(msg, category=FutureWarning)

[[1 0 0 ... 0 0 0]
 [0 1 2 ... 0 0 0]
 [0 0 0 ... 0 0 0]
 ...
 [0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]]

-------------------------

TF-IDF
[6.44924025 5.79159976 3.00777917 ... 5.43131687 5.60527018 6.33923936]
10000

-------------------------

Predictions
[1 1 1 ... 1 0 0]


---- Classification report ----
              precision    recall  f1-score   support

     positif       0.89      0.85      0.87      1280
     negatif       0.85      0.89      0.87      1220

    accuracy                           0.87      2500
   macro avg       0.87      0.87      0.87      2500
weighted avg       0.87      0.87      0.87      2500

Outils de prétraitement: NLTK

On va maintenant chercher à pré-traiter nos données de manière à simplifier la tâche du modèle. Notez toujours que celà ne sera probablement utile que si l'on a trop peu de données à disposition !

Stemming:

Permet de revenir à la racine d'un mot: on peut ainsi grouper différents mots autour de la même racine, ce qui facilite la généralisation. On peut utiliser l'outil SnowballStemmer.

from nltk import SnowballStemmer
stemmer = SnowballStemmer("english")

Exemple d'utilisation:

words = ['singers', 'cat', 'generalization', 'philosophy', 'psychology', 'philosopher']
for word in words:
    print('word : %s ; stemmed : %s' %(word, stemmer.stem(word)))#.decode('utf-8'))))

word : singers ; stemmed : singer
word : cat ; stemmed : cat
word : generalization ; stemmed : general
word : philosophy ; stemmed : philosophi
word : psychology ; stemmed : psycholog
word : philosopher ; stemmed : philosoph

Transformation des données:

def stem(word): 
# To complete
  stemmer = SnowballStemmer("english")
  word_stemmed = stemmer.stem(word)

  result = [word, word_stemmed]
  return result

Test de la fonction stem

# Test it on the dataset
sentence = train_texts_reduced[0] # test on the first sentence of our dataset
print("--- Original sentence ---")
print(sentence)

list_words = sentence.split(" ")

list_word_stemmed = list()
for word in list_words:
  stemmed_word = stem(word)
  list_word_stemmed.append(stemmed_word)

print("\n\n--- Stemmed words ---")
list_word_stemmed

--- Original sentence ---
Story of a man who has unnatural feelings for a pig. Starts out with a opening scene that is a terrific example of absurd comedy. A formal orchestra audience is turned into an insane, violent mob by the crazy chantings of it's singers. Unfortunately it stays absurd the WHOLE time with no general narrative eventually making it just too off putting. Even those from the era should be turned off. The cryptic dialogue would make Shakespeare seem easy to a third grader. On a technical level it's better than you might think with some good cinematography by future great Vilmos Zsigmond. Future stars Sally Kirkland and Frederic Forrest can be seen briefly.


--- Stemmed words ---

[['Story', 'stori'],
 ['of', 'of'],
 ['a', 'a'],
 ['man', 'man'],
 ['who', 'who'],
 ['has', 'has'],
 ['unnatural', 'unnatur'],
 ['feelings', 'feel'],
 ['for', 'for'],
 ['a', 'a'],
 ['pig.', 'pig.'],
 ['Starts', 'start'],
 ['out', 'out'],
 ['with', 'with'],
 ['a', 'a'],
 ['opening', 'open'],
 ['scene', 'scene'],
 ['that', 'that'],
 ['is', 'is'],
 ['a', 'a'],
 ['terrific', 'terrif'],
 ['example', 'exampl'],
 ['of', 'of'],
 ['absurd', 'absurd'],
 ['comedy.', 'comedy.'],
 ['A', 'a'],
 ['formal', 'formal'],
 ['orchestra', 'orchestra'],
 ['audience', 'audienc'],
 ['is', 'is'],
 ['turned', 'turn'],
 ['into', 'into'],
 ['an', 'an'],
 ['insane,', 'insane,'],
 ['violent', 'violent'],
 ['mob', 'mob'],
 ['by', 'by'],
 ['the', 'the'],
 ['crazy', 'crazi'],
 ['chantings', 'chant'],
 ['of', 'of'],
 ["it's", 'it'],
 ['singers.', 'singers.'],
 ['Unfortunately', 'unfortun'],
 ['it', 'it'],
 ['stays', 'stay'],
 ['absurd', 'absurd'],
 ['the', 'the'],
 ['WHOLE', 'whole'],
 ['time', 'time'],
 ['with', 'with'],
 ['no', 'no'],
 ['general', 'general'],
 ['narrative', 'narrat'],
 ['eventually', 'eventu'],
 ['making', 'make'],
 ['it', 'it'],
 ['just', 'just'],
 ['too', 'too'],
 ['off', 'off'],
 ['putting.', 'putting.'],
 ['Even', 'even'],
 ['those', 'those'],
 ['from', 'from'],
 ['the', 'the'],
 ['era', 'era'],
 ['should', 'should'],
 ['be', 'be'],
 ['turned', 'turn'],
 ['off.', 'off.'],
 ['The', 'the'],
 ['cryptic', 'cryptic'],
 ['dialogue', 'dialogu'],
 ['would', 'would'],
 ['make', 'make'],
 ['Shakespeare', 'shakespear'],
 ['seem', 'seem'],
 ['easy', 'easi'],
 ['to', 'to'],
 ['a', 'a'],
 ['third', 'third'],
 ['grader.', 'grader.'],
 ['On', 'on'],
 ['a', 'a'],
 ['technical', 'technic'],
 ['level', 'level'],
 ["it's", 'it'],
 ['better', 'better'],
 ['than', 'than'],
 ['you', 'you'],
 ['might', 'might'],
 ['think', 'think'],
 ['with', 'with'],
 ['some', 'some'],
 ['good', 'good'],
 ['cinematography', 'cinematographi'],
 ['by', 'by'],
 ['future', 'futur'],
 ['great', 'great'],
 ['Vilmos', 'vilmo'],
 ['Zsigmond.', 'zsigmond.'],
 ['Future', 'futur'],
 ['stars', 'star'],
 ['Sally', 'salli'],
 ['Kirkland', 'kirkland'],
 ['and', 'and'],
 ['Frederic', 'freder'],
 ['Forrest', 'forrest'],
 ['can', 'can'],
 ['be', 'be'],
 ['seen', 'seen'],
 ['briefly.', 'briefly.']]

Construction d'une fonction de preprocessing pour stemmatiser notre corpus de texte

def preprocess_stem(text):
    list_words = text.split(" ")
    
    text_ = ' '.join([stemmer.stem(word) for word in list_words])

    return text_

On applique la fonction de preprocessing

text_train_stemmed = list()
for elm in train_texts_splt:
  elm_preprocessed = preprocess_stem(elm)
  text_train_stemmed.append(elm_preprocessed)

print(len(text_train_stemmed))

10000

On appique la pipeline {CountVectorizer, TF-IDF, MultinomialNB}

pipe = Pipeline([('vec_count', CountVectorizer(max_features= 10000, analyzer='word', max_df=0.2, ngram_range=(1,3))), 
                 ('tfidf', TfidfTransformer()),
                 ('clf', MultinomialNB())
                 ])

pipe.fit(text_train_stemmed, train_labels_splt)

print("features names")
feat_names = pipe['vec_count'].get_feature_names()

print("\n-------------------------\n")

print("Vocabulary")
vocab = pipe['vec_count'].vocabulary_
print(vocab)

print("\n-------------------------\n")

print("CountVectorizer")
vec_count = pipe['vec_count'].transform(text_train_stemmed).toarray()
print(vec_count)

print("\n-------------------------\n")

print("TF-IDF")
tf_idf = pipe['tfidf'].idf_
print(tf_idf)
print(len(tf_idf))

print("\n-------------------------\n")

# Make predictions
predictions = pipe.predict(val_texts)

print("Predictions")
print(predictions)

# Show the results in a readable format
print("\n\n---- Classification report ----")

report_classification = classification_report(val_labels, predictions, target_names=["positif", "negatif"], output_dict=True)

print(classification_report(val_labels, predictions, target_names=["positif", "negatif"]))

cm = confusion_matrix(val_labels, predictions)
cm_disp = ConfusionMatrixDisplay(cm, display_labels=["positif", "negatif"])

cm_disp.plot()
plt.show()

features names

-------------------------

Vocabulary
{'saw': 6760, 'becam': 1057, 'ever': 2584, 'walk': 9280, 'middle': 5190, 'noth': 5621, 'wors': 9822, 'comedi': 1867, 'miss': 5221, 'funny': 3132, 'everi': 2589, 'although': 313, 'speak': 7243, 'last': 4704, '25': 41, 'minut': 5212, 'origin': 6006, 'while': 9617, 'enjoy': 2502, 'humor': 3814, 'where': 9575, 'these': 8415, 'skit': 7100, 'needless': 5487, 'vulgar': 9272, 'irrit': 4127, 'advertis': 175, 'robin': 6673, 'william': 9698, 'capit': 1640, 'new': 5509, 'found': 3057, 'fame': 2709, 'televis': 7543, 'series': 6931, 'yet': 9904, 'role': 6679, 'turn': 9061, 'minor': 5211, 'cannot': 1635, 'notic': 5633, 'screen': 6830, 'when saw': 9565, 'saw this': 6763, 'this movie': 8579, 'the first': 7911, 'first movi': 2915, 'movi that': 5352, 'walk out': 9283, 'out of': 6046, 'there is': 8390, 'is noth': 4232, 'wors than': 9823, 'comedi that': 1869, 'that just': 7647, 'be funny': 1018, 'funny and': 3133, 'and this': 580, 'everi time': 2593, 'the last': 7993, 'minut of': 5214, 'the movie': 8062, 'movie there': 5381, 'there was': 8408, 'was noth': 9358, 'about ani': 64, 'ani of': 636, 'what was': 9550, 'was even': 9334, 'even more': 2569, 'was that': 9382, 'that this': 7693, 'movi was': 5358, 'first movie': 2916, 'on his': 5877, 'his new': 3711, 'his role': 3714, 'turn out': 9067, 'out to': 6058, 'be so': 1035, 'that you': 7713, 'on screen': 5887, 'the first movi': 7914, 'there is noth': 8395, 'minut of the': 5215, 'of the movie': 5784, 'ani of the': 637, 'that this movi': 7696, 'this movi was': 8576, 'turn out to': 9068, 'out to be': 6059, 'next': 5513, 'action': 126, 'star': 7295, 'realiti': 6512, 'tv': 9073, 'tape': 7522, 'aw': 921, 'bizarr': 1194, 'reason': 6530, 'myself': 5450, 'blame': 1200, 'whole': 9665, 'hope': 3751, 'something': 7206, 'uniqu': 9130, 'entir': 2524, 'hype': 3824, 'silver': 7061, 'touch': 8994, 'flicks': 2943, 'might': 5192, 'sure': 7461, 'bone': 1231, 'redeem': 6553, 'valu': 9194, 'billi': 1183, 'couldn': 1993, 'lift': 4800, 'write': 9868, 'said': 6731, 'perform': 6166, 'through': 8656, 'doesn': 2293, 'els': 2454, 'here': 3626, 'though': 8632, 'writing': 9874, 'quit': 6457, 'frankly': 3073, 'sucked': 7433, 'let': 4771, 'take': 7495, 'idea': 3828, 'rat': 6479, 'race': 6462, 'enemi': 2495, 'state': 7313, 'midnight': 5191, 'run': 6710, 'simpli': 7067, 'brilliant': 1431, 'two': 9084, 'bridg': 1428, 'chase': 1747, 'sequenc': 6920, 'row': 6704, 'sean': 6846, 'man': 5034, 'hour': 3775, 'strength': 7383, 'weak': 9476, 'cast': 1666, 'director': 2231, 'mention': 5166, 'dure': 2393, 'dumb': 2390, 'struggl': 7394, 'shoulder': 7021, 'weight': 9485, 'care': 1649, 'whether': 9585, 'live': 4866, 'die': 2204, 'mid': 5186, 'fail': 2694, 'provid': 6412, 'audienc': 905, 'lucki': 4958, 'routin': 6703, 'old': 5859, 'isn': 4317, 'anyth': 667, 'root': 6698, 'dream': 2365, 'compar': 1894, 'wooden': 9790, 'van': 9198, 'de': 2092, 'did': 2185, 'howard': 3798, 'fine': 2906, 'tell': 7545, 'pretend': 6346, 'half': 3394, 'kept': 4624, 'expect': 2643, 'quot': 6461, 'performance': 6177, 'dramat': 2360, 'depth': 2142, 'freddi': 3076, 'got': 3298, 'near': 5472, 'camera': 1595, 'dark': 2076, 'harsh': 3432, 'light': 4801, 'day': 2087, 'suck': 7432, 'energi': 2496, 'off': 5832, 'natur': 5465, 'life': 4787, 'five': 2931, 'bit': 1188, 'part': 6113, 'lead': 4731, 'ensembl': 2516, 'shouldn': 7022, 'left': 4754, 'solo': 7170, 'big': 1176, 'task': 7525, 'may': 5098, 'better': 1151, 'luck': 4957, 'dynam': 2399, 'hard': 3427, 'given': 3224, 'jeff': 4534, 'lame': 4695, 'script': 6837, 'someon': 7194, 'should': 7016, 'away': 927, 'befor': 1088, 'hurt': 3821, 'himself': 3679, 'anyon': 663, 'else': 2457, 'finally': 2893, 'reach': 6491, 'complet': 1905, 'after watch': 197, 'mani of': 5047, 'the next': 8080, 'for me': 2990, 'me for': 5115, 'for some': 3001, 'reason and': 6531, 'and onli': 514, 'watch the': 9423, 'the whole': 8309, 'whole thing': 9670, 'hope that': 3754, 'that there': 7687, 'would be': 9840, 'the entir': 7869, 'so much': 7141, 'he might': 3551, 'want to': 9291, 'to make': 8839, 'make sure': 5017, 'up on': 9158, 'br first': 1351, 'first the': 2923, 'the onli': 8090, 'entir film': 2525, 'film was': 2872, 'and even': 426, 'have said': 3500, 'said that': 6733, 'the way': 8299, 'way through': 9451, 'as he': 783, 'he doesn': 3532, 'doesn even': 2294, 'seem to': 6888, 'to know': 8827, 'know what': 4666, 'els to': 2456, 'to do': 8773, 'other than': 6024, 'br can': 1346, 'though the': 8636, 'the state': 8225, 'film you': 2882, 'you can': 9917, 'can think': 1625, 'think of': 8493, 'of and': 5680, 'it and': 4335, 'and who': 610, 'was it': 9345, 'it to': 4476, 'to have': 8810, 'the man': 8026, 'man of': 5038, 'hour of': 3778, 'all of': 259, 'the cast': 7784, 'dure the': 2394, 'the series': 8199, 'play the': 6247, 'good look': 3281, 'veri well': 9219, 'well but': 9494, 'we never': 9471, 'to care': 8755, 'care about': 1650, 'fail to': 2695, 'reason for': 6532, 'the audienc': 7738, 'to even': 8784, 'like him': 4811, 'as there': 819, 'there realli': 8404, 'anyth about': 668, 'about the': 72, 'the charact': 7793, 'charact to': 1727, 'root for': 6699, 'br but': 1344, 'compar to': 1896, 'tell her': 7546, 'her to': 3625, 'pretend to': 6347, 'first half': 2914, 'half of': 3396, 'don think': 2322, 'her charact': 3608, 'can be': 1602, 'onli to': 5966, 'depth of': 2143, 'though not': 8635, 'not near': 5594, 'near as': 5473, 'as well': 828, 'the camera': 7779, 'love her': 4938, 'her in': 3615, 'but in': 1498, 'off the': 5841, 'the screen': 8188, 'life in': 4793, 'in her': 3924, 'five minut': 2932, 'at ani': 862, 'part of': 6117, 'of her': 5704, 'screen time': 6833, 'time br': 8682, 'has the': 3455, 'look to': 4907, 'in an': 3900, 'have been': 3470, 'left to': 4757, 'do this': 2275, 'this one': 8586, 'for him': 2983, 'may not': 5102, 'not have': 5584, 'have had': 3484, 'with some': 9742, 'some more': 7176, 'but it': 1503, 'it hard': 4386, 'hard to': 3428, 'to tell': 8914, 'away from': 929, 'from him': 3095, 'befor he': 1090, 'way out': 9446, 'even for': 2562, 'like this': 4825, 'this br': 8510, 'should be': 7017, 'mani of the': 5048, 'the whole thing': 8313, 'want to make': 9297, 'br br first': 1300, 'the entir film': 7870, 'out of the': 6051, 'of the way': 5798, 'the way through': 8305, 'br br can': 1295, 'can think of': 1626, 'all of the': 260, 'of the film': 5774, 'br br but': 1294, 'compar to the': 1897, 'for the first': 3010, 'the first half': 7913, 'half of the': 3397, 'but in the': 1499, 'time br br': 8683, 'it hard to': 4387, 'this br br': 8511, 'african': 185, 'american': 329, 'classic': 1811, 'comedy': 1872, 'cult': 2047, 'recent': 6541, 'purchas': 6427, 'collect': 1840, 'edit': 2425, 'ray': 6489, 'school': 6814, 'black': 1195, 'comedies': 1871, 'anymore': 662, 'famili': 2710, 'site': 7090, 'extrem': 2672, 'help': 3592, 'solv': 7171, 'am': 321, 'right': 6655, 'now': 5638, 'stay': 7319, 'connect': 1929, 'world': 9815, 'thank': 7584, 'imdb': 3878, 'recommend': 6543, 'friends': 3088, 'word': 9794, 'check': 1751, 'yourself': 9993, 'ten': 7553, 'line': 4840, 'lot': 4921, 'comment': 1879, 'point': 6269, 'across': 111, 'not onli': 5597, 'is this': 4291, 'this great': 8536, 'african american': 186, 'but one': 1519, 'of mani': 5725, 'you love': 9949, 'love the': 4944, 'the old': 8086, 'movi and': 5299, 'is for': 4184, 'for you': 3029, 'they don': 8436, 'don make': 2318, 'make movi': 5010, 'movi like': 5334, 'like these': 4823, 'so this': 7151, 'this site': 8603, 'is an': 4140, 'an extrem': 362, 'right now': 6658, 'me to': 5124, 'to stay': 8908, 'connect to': 1930, 'thank you': 7586, 'recommend this': 6546, 'to all': 8724, 'for it': 2986, 'out for': 6040, 'for yourself': 3031, 'line is': 4843, 'is lot': 4215, 'comment on': 1880, 'on one': 5886, 'but if': 1496, 'if it': 3840, 'it get': 4379, 'get the': 3195, 'the point': 8131, 'outsid': 6064, 'room': 6697, 'real': 6502, 'costum': 1980, 'string': 7388, 'porn': 6295, 'worth': 9831, 'between': 1166, 'sex': 6952, 'scenes': 6811, 'cinema': 1791, 'is realli': 4258, 'not in': 5586, 'you have': 9936, 'have to': 3511, 'to see': 8888, 'see this': 6875, 'movie it': 5375, 'it the': 4471, 'know that': 4663, 'that is': 7638, 'is worth': 4313, 'worth watch': 9835, 'between the': 1167, 'the sex': 8201, 'you have to': 9937, 'have to see': 3515, 'to see this': 8895, 'see this movie': 6878, 'this movie it': 8583, 'theater': 8339, 'came': 1589, 'grew': 3338, 'went': 9507, 'locat': 4886, 'spent': 7257, 'rememb': 6591, 'barbara': 987, 'rock': 6676, 'sound': 7230, 'actual': 149, 'success': 7424, 'fan': 2716, 'sing': 7079, 'until': 9141, 'effort': 2439, 'west': 9523, 'actor': 134, 'serious': 6932, 'romance': 6691, 'version': 9221, 'original': 6009, 'believ': 1112, 'chang': 1706, 'long': 4891, 'dvd': 2397, 'release': 6578, 'among': 332, 'things': 8485, 'recal': 6539, 'shot': 7009, 'reveal': 6637, 'pack': 6090, 'sun': 7448, 'devil': 2174, 'longer': 4895, 'wish': 9711, 'done': 2330, 'job': 4547, 'music': 5421, 'god': 3254, 'put': 6434, 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'that it would': 7646, 'was his': 9342, 'most import': 5276, 'is wast': 4303, 'ever see': 2586, 'speci': 7245, 'in few': 3917, 'however is': 3802, 'scale': 6781, 'someth else': 7200, 'no other': 5536, 'fix': 2933, 'plot the': 6263, 'song are': 7218, 'panic': 6101, 'weak and': 9477, 'suspens and': 7479, 'lead man': 4733, 'st': 7282, 'took the': 8983, 'movie it was': 5377, 'to watch and': 8943, 'psychic': 6415, 'company': 1893, 'score is': 6826, 'they must': 8451, 'dirti': 2237, 'br at': 1278, 'have no idea': 3493, 'br br at': 1291, 'ritter': 6666, 'adequ': 163, 'the success': 8239, 'an all': 345, 'off br': 5835, 'off br br': 5836, 'go in': 3242, 'they come': 8428, 'you see the': 9960, 'karen': 4612, 'what could': 9529, 'out br': 6036, 'out br br': 6037, 'ugly': 9095, 'film seen': 2860, 'br out': 1378, 'br br out': 1322, 'br out of': 1379, 'fourth': 3066, 'hate the': 3463, 'place the': 6228, 'director who': 2234, 'pound': 6316, 'can have': 1611, 'bus': 1468, 'oil': 5855, 'usa': 9179, 'but at the': 1478, 'mexico': 5180, 'earl': 2405, 'viewing': 9248, 'as such': 814, 'can easili': 1605, 'times br': 8707, 'times br br': 8708, 'awesom': 934, 'communic': 1888, 'she goe': 6982, 'time as': 8681, 'and both': 401, 'swim': 7485, 'with two': 9755, 'naturally': 5468, 'of action': 5674, 'here we': 3640, 'iran': 4122, 'have good': 3482, 'sinc this': 7076, 'in the series': 3999, 'the dialog': 7836, 'mann': 5056, 'also be': 306, 'driver': 2375, 'torment': 8988, 'bradi': 1413, 'and leav': 481, 'of whom': 5826, 'babe': 938, 'could see': 1992, 'hero and': 3642, 'foul': 3056, 'natali': 5462, 'depart': 2136, 'trip to': 9045, 'thought was': 8646, 'bourn': 1257, 'the entir movi': 7871, 'have gone': 3481, 'film or': 2856, 'stomach': 7347, 'wish that': 9712, 'ed wood': 2420, 'follow by': 2957, 'inherit': 4055, 'for sure': 3006, 'in case': 3908, 'plot that': 6262, 'didn care': 2196, 'victoria': 9236, 'peopl in the': 6151, 'hamlet': 3404, 'branagh': 1415, 'the husband': 7971, 'icon': 3827, 'earli on': 2407, 'said the': 6734, 'talent and': 7514, 'is better': 4154, 'sens of humor': 6911, 'so if you': 7136, 'give this film': 3219, 'to our': 8859, 'navi': 5470, 'inside': 4063, 'unforgett': 9122, 'guns': 3367, 'derek': 2144, 'what the hell': 9545, 'spielberg': 7259, 'this show is': 8602, 'vision of': 9261, 'it is about': 4397, 'anticip': 659, 'substanc': 7418, 'know he': 4658, 'the heart of': 7954, 'the mind': 8040, 'movi of all': 5340, 'nuclear': 5647, 'dark and': 2077, 'disguis': 2251, 'off his': 5838, 'dialog is': 2178, 'explain the': 2658, 'han': 3406, 'whi doe': 9592, 'if it were': 3842, 'this is what': 8551, 'even if it': 2566, 'for everyone': 2976, 'while watch': 9624, 'lane': 4698, 'walk around': 9281, 'ruthless': 6722, 'or to': 5998, 'than anyth': 7573, 'height': 3588, 'dire': 2222, 'absorb': 91, 'they find': 8438, 'screen in': 6832, 'this man': 8559, 'tarzan': 7524, 'he not': 3555, 'the dog': 7846, 'to get to': 8803, 'the daughter': 7829, 'dose': 2341, 'and john': 474, 'his mind': 3707, 'the media': 8034, 'never see': 5506, 'and lack': 478, 'on me': 5884, 'punk': 6426, 'it kind': 4412, 'too br': 8972, 'too br br': 8973, 'confusing': 1928, 'emerg': 2463, 'more on': 5267, 'an adult': 344, 'safe': 6729, 'muslim': 5428, '70s': 51, 'wet': 9525, 'seagal': 6845, 'blast': 1203, 'inspector': 4067, 'reach the': 6492, 'elvi': 2459, 'diamond': 2183, 'rob roy': 6671, 'and his wife': 460, 'in the final': 3982, 'farm': 2735, 'next time': 5514, 'jake': 4522, 'jungl': 4576, 'firm': 2911, 'miik': 5197, 'punish': 6425, 'timon': 8710, 'in common': 3910, 'his family': 3695, 'virginia': 9257, 'your heart': 9987, 'grinch': 3344, 'the grinch': 7944, 'ruth': 6721, 'neo': 5495, 'kill them': 4641, 'is better than': 4155, 'betti page': 1165, 'che': 1748}

-------------------------

CountVectorizer

/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function get_feature_names is deprecated; get_feature_names is deprecated in 1.0 and will be removed in 1.2. Please use get_feature_names_out instead.
  warnings.warn(msg, category=FutureWarning)

[[0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]
 ...
 [0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]
 [0 0 0 ... 0 1 0]]

-------------------------

TF-IDF
[6.52156091 5.76778911 3.00703485 ... 6.68407984 6.1673891  6.18508868]
10000

-------------------------

Predictions
[1 0 1 ... 1 0 1]


---- Classification report ----
              precision    recall  f1-score   support

     positif       0.84      0.85      0.85      1267
     negatif       0.84      0.84      0.84      1233

    accuracy                           0.84      2500
   macro avg       0.84      0.84      0.84      2500
weighted avg       0.84      0.84      0.84      2500

Partie du discours

Pour généraliser, on peut aussi utiliser les parties du discours (Part of Speech, POS) des mots, ce qui nous permettra de filtrer l'information qui n'est potentiellement pas utile au modèle. On va récupérer les POS des mots à l'aide des fonctions pos_tag, word_tokenize.

import nltk
from nltk import pos_tag, word_tokenize

Exemple d'utilisation:

import nltk
nltk.download('punkt')
nltk.download('averaged_perceptron_tagger')

pos_tag(word_tokenize(('I am Sam')))

[nltk_data] Downloading package punkt to /root/nltk_data...
[nltk_data]   Unzipping tokenizers/punkt.zip.
[nltk_data] Downloading package averaged_perceptron_tagger to
[nltk_data]     /root/nltk_data...
[nltk_data]   Unzipping taggers/averaged_perceptron_tagger.zip.

[('I', 'PRP'), ('am', 'VBP'), ('Sam', 'NNP')]

Transformation des données:

Ne garder que les noms, adverbes, verbes et adjectifs (['NN', 'VB', 'ADJ', 'RB']) pour notre modèle.

def pos_tag_filter(sentence, good_tags=['NN', 'VB', 'ADJ', 'RB']):
# To complete !
  sentence_tokenized = word_tokenize(sentence)

  list_tag = pos_tag(sentence_tokenized)

  list_accepted_pos_tag = list()

  for tag in list_tag:
    if tag[1] in good_tags:
      list_accepted_pos_tag.append(tag)
  
  return list_accepted_pos_tag

Test de la fonction pos_tagfilter

# Test it on the dataset
sentence = train_texts_reduced[0] # test on the first sentence of our dataset
print("--- Original phrase ---")
print(sentence)

print("\n\n--- Pos Tags ---")
pos_tag_filter(sentence)

--- Original phrase ---
Story of a man who has unnatural feelings for a pig. Starts out with a opening scene that is a terrific example of absurd comedy. A formal orchestra audience is turned into an insane, violent mob by the crazy chantings of it's singers. Unfortunately it stays absurd the WHOLE time with no general narrative eventually making it just too off putting. Even those from the era should be turned off. The cryptic dialogue would make Shakespeare seem easy to a third grader. On a technical level it's better than you might think with some good cinematography by future great Vilmos Zsigmond. Future stars Sally Kirkland and Frederic Forrest can be seen briefly.


--- Pos Tags ---

[('Story', 'NN'),
 ('man', 'NN'),
 ('pig', 'NN'),
 ('opening', 'NN'),
 ('scene', 'NN'),
 ('example', 'NN'),
 ('comedy', 'NN'),
 ('orchestra', 'NN'),
 ('audience', 'NN'),
 ('insane', 'NN'),
 ('mob', 'NN'),
 ('Unfortunately', 'RB'),
 ('time', 'NN'),
 ('eventually', 'RB'),
 ('just', 'RB'),
 ('too', 'RB'),
 ('Even', 'RB'),
 ('era', 'NN'),
 ('be', 'VB'),
 ('dialogue', 'NN'),
 ('make', 'VB'),
 ('seem', 'VB'),
 ('grader', 'NN'),
 ('level', 'NN'),
 ('think', 'VB'),
 ('cinematography', 'NN'),
 ('be', 'VB'),
 ('briefly', 'NN')]

Construction d'une fonction de preprocessing pour stemmatiser et filter les tags notre corpus de texte

def preprocess_stem_filter(text):
    list_words = text.split(" ")
    
    # on stemmatise la phrase
    text_1 = ' '.join([stemmer.stem(word) for word in list_words])

    # On garde uniquement les mots associés aux bons tags
    text_2 = pos_tag_filter(text_1, good_tags=['NN', 'VB', 'ADJ', 'RB'])

    # Reconstruction la phrase
    text_3 = " ".join([i[0] for i in text_2])

    return text_3

text_train_stemmed_filtered = list()
for elm in train_texts_splt:
  elm_preprocessed = preprocess_stem_filter(elm)
  text_train_stemmed_filtered.append(elm_preprocessed)

print(len(text_train_stemmed_filtered))

10000

On appique la pipeline {CountVectorizer, TF-IDF, MultinomialNB}

pipe = Pipeline([('vec_count', CountVectorizer(max_features= 10000, analyzer='word', max_df=0.2, ngram_range=(1,3))), 
                 ('tfidf', TfidfTransformer()),
                 ('clf', MultinomialNB())
                 ])

pipe.fit(text_train_stemmed_filtered, train_labels_splt)

print("features names")
feat_names = pipe['vec_count'].get_feature_names()

print("\n-------------------------\n")

print("Vocabulary")
vocab = pipe['vec_count'].vocabulary_
print(vocab)

print("\n-------------------------\n")

print("CountVectorizer")
vec_count = pipe['vec_count'].transform(text_train_stemmed_filtered).toarray()
print(vec_count)

print("\n-------------------------\n")

print("TF-IDF")
tf_idf = pipe['tfidf'].idf_
print(tf_idf)
print(len(tf_idf))

print("\n-------------------------\n")

# Make predictions
predictions = pipe.predict(val_texts)

print("Predictions")
print(predictions)

# Show the results in a readable format
print("\n\n---- Classification report ----")

report_classification = classification_report(val_labels, predictions, target_names=["positif", "negatif"], output_dict=True)

print(classification_report(val_labels, predictions, target_names=["positif", "negatif"]))

cm = confusion_matrix(val_labels, predictions)
cm_disp = ConfusionMatrixDisplay(cm, display_labels=["positif", "negatif"])

cm_disp.plot()
plt.show()

features names

-------------------------

Vocabulary
{'ever': 3173, 'middle': 5778, 'comedi': 2125, 'everi': 3195, 'speak': 8415, 'minut': 5817, 'origin': 6657, 'ani': 341, 'humor': 4576, 'vulgar': 9538, 'irrit': 4805, 'advertis': 152, 'robin': 7647, 'william': 9803, 'capit': 1734, 'fame': 3332, 'televis': 8851, 'series': 8017, 'role': 7667, 'movi ever': 6004, 'just be': 4961, 'everi time': 3200, 'minut movie': 5824, 'robin william': 7648, 'role be': 7668, 'be so': 789, 'so not': 8307, 'not even': 6394, 'mani': 5609, 'action': 84, 'star': 8495, 'tv': 9336, 'tape': 8818, 'tripe': 9303, 'bizarr': 971, 'reason': 7409, 'blame': 982, 'something': 8366, 'uniqu': 9386, 'hype': 4594, 'joel': 4905, 'silver': 8165, 'touch': 9226, 'want': 9561, 'first': 3717, 'onli': 6616, 'valu': 9418, 'entir': 3076, 'zane': 9989, 'lift': 5315, 'perform': 6857, 'seem': 7979, 'know': 5130, 'do': 2728, 'here': 4391, 'though': 9040, 'writing': 9921, 'quit': 7289, 'frankly': 3824, 'let': 5260, 'take': 8792, 'idea': 4600, 'rat': 7335, 'race': 7297, 'enemi': 3032, 'state': 8515, 'run': 7726, 'gambl': 3891, 'think': 9014, 'simpli': 8171, 'rehash': 7468, 'chase': 1928, 'sequenc': 8007, 'row': 7714, 'man': 5583, 'hour': 4539, 'strength': 8636, 'cast': 1784, 'director': 2655, 'mention': 5739, 'dure': 2865, 'jock': 4901, 'veri': 9447, 'shoulder': 8112, 'weight': 9700, 'never': 6285, 'care': 1746, 'die': 2622, 'mid': 5773, 'through': 9051, 'provid': 7231, 'audienc': 526, 'routin': 7712, 'realli': 7381, 'root': 7701, 'dream': 2821, 'compar': 2161, 'wooden': 9849, 'van': 9424, 'howard': 4553, 'tell': 8854, 'pretend': 7142, 'termin': 8873, 'half': 4207, 'quot': 7295, 'performance': 6868, 'dramat': 2817, 'depth': 2565, 'camera': 1708, 'dark': 2455, 'light': 5316, 'day': 2469, 'suck': 8692, 'screen': 7892, 'bauer': 657, 'show': 8115, 'life': 5289, 'bit': 958, 'part': 6752, 'ultimately': 9365, 'lead': 5227, 'ensembl': 3063, 'solo': 8348, 'task': 8823, 'colleagu': 2098, 'jare': 4855, 'elliot': 2961, 'luck': 5487, 'characterization': 1915, 'jeff': 4865, 'welch': 9703, 'script': 7902, 'someon': 8355, 'away': 558, 'befor': 864, 'hurt': 4588, 'anyon': 381, 'else': 2963, 'finally': 3698, 'reach': 7364, 'complet': 2175, 'action star': 93, 'thing be': 8979, 'movie so': 6164, 'want make': 9567, 'br first': 1374, 'entir film': 3077, 'way even': 9655, 'know do': 5136, 'do br': 2732, 'film think': 3664, 'cast director': 1792, 'veri well': 9468, 'film quit': 3620, 'pretend be': 7143, 'half film': 4208, 'think so': 9026, 'be onli': 758, 'show life': 8130, 'part br': 6755, 'cast have': 1794, 'have do': 4281, 'not have': 6417, 'anyon else': 382, 'br br first': 1184, 'do br br': 2733, 'part br br': 6756, 'comedy': 2131, 'cult': 2397, 'edit': 2919, 'ray': 7357, 'moore': 5917, 'if': 4617, 'school': 7865, 'karat': 5052, 'anymore': 380, 'famili': 3333, 'site': 8200, 'extrem': 3287, 'help': 4375, 'right': 7611, 'now': 6525, 'stay': 8520, 'world': 9881, 'thank': 8894, 'recommend': 7433, 'word': 9852, 'check': 1934, 'line': 5335, 'lot': 5428, 'comment': 2140, 'point': 7045, 'not comedy': 6383, 'movi make': 6045, 'right now': 7616, 'just take': 5025, 'comment movi': 2145, 'movi point': 6071, 'outsid': 6689, 'motel': 5936, 'room': 7698, 'costum': 2289, 'string': 8640, 'sex': 8039, 'scenes': 7858, 'cinema': 2003, 'not onli': 6453, 'see movie': 7962, 'movie movi': 6151, 'movi watch': 6119, 'scenes br': 7859, 'cinema br': 2004, 'scenes br br': 7860, 'cinema br br': 2005, 'theater': 8902, 'arizona': 431, 'enjoy': 3045, 'rememb': 7493, 'barbara': 622, 'ventur': 9443, 'rock': 7653, 'sound': 8400, 'success': 8689, 'fan': 3338, 'effort': 2935, 'west': 9751, 'actor': 96, 'romance': 7687, 'judi': 4944, 'garland': 3909, 'version': 9469, 'janet': 4852, 'chang': 1859, 'dvd': 2879, 'release': 7479, 'helicopt': 4369, 'shot': 8109, 'pack': 6712, 'sun': 8711, 'devil': 2608, 'stadium': 8475, 'wish': 9820, 'job': 4896, 'music': 6210, 'kris': 5154, 'god': 4086, 'song': 8376, 'there': 8953, 'inform': 4700, 'primari': 7156, 'sourc': 8405, 'problem': 7175, 'interview': 4780, 'documentary': 2756, 'boat': 1013, 'journey': 4934, 'stephen': 8530, 'singer': 8186, 'profession': 7197, 'person': 6883, 'tie': 9065, 'bonni': 1033, 'john': 4907, 'band': 616, 'turn': 9327, 'pop': 7073, 'score': 7881, 'pass': 6774, 'friend': 3834, 'member': 5731, 'tension': 8871, 'set': 8027, 'presence': 7132, 'effect': 2927, 'talk': 8813, 'back': 576, 'roll': 7683, 'around': 439, 'decid': 2505, 'use': 9400, 'work': 9856, 'gain': 3887, 'respect': 7540, 'artist': 455, 'hear': 4348, 'story': 8610, 'gay': 3915, 'movi theater': 6100, 'realli enjoy': 7385, 'so time': 8330, 'rememb time': 7494, 'judi garland': 4945, 'dvd release': 2884, 'there br': 8956, 'br line': 1410, 'rock roll': 7656, 'perform movi': 6866, 'thing work': 9013, 'boy': 1079, 'interest': 4753, 'creat': 2342, 'mom': 5875, 'video': 9488, 'love': 5450, 'attempt': 511, 'pathet': 6785, 'as': 457, 'mean': 5707, 'hey': 4419, 'budget': 1637, 'flick': 3746, 'still': 8541, 'case': 1776, 'doom': 2780, 'taste': 8825, 'perhap': 6871, 'awak': 554, 'one': 6604, 'br interest': 1397, 'interest thing': 4769, 'thing movi': 8999, 'effect use': 2934, 'even way': 3166, 'way so': 9674, 'so love': 8300, 'love movie': 5463, 'movie br': 6132, 'br not': 1443, 'not end': 6391, 'as well': 468, 'still make': 8556, 'make movi': 5554, 'movi budget': 5983, 'budget movi': 1641, 'br br interest': 1203, 'movie br br': 6133, 'br br not': 1237, 'cartoon': 1773, 'background': 594, 'color': 2107, 'art': 447, 'anim': 349, 'studio': 8654, 'standard': 8490, 'however': 4556, 'number': 6549, 'scott': 7887, 'suppos': 8735, 'setting': 8032, 'up': 9392, 'monoton': 5903, 'sinc': 8179, 'includ': 4669, 'close': 2059, 'eye': 3290, 'averag': 547, 'viewer': 9496, 'storyline': 8620, 'give': 4029, 'secret': 7929, 'alreadi': 254, 'countri': 2296, 'theme': 8910, 'era': 3094, 'nostalgia': 6359, 'lot be': 5430, 'br music': 1437, 'music not': 6218, 'suppos be': 8736, 'not give': 6414, 'br br music': 1232, 'doubt': 2788, 'about': 10, 'year': 9936, 'sometim': 8369, 'rape': 7331, 'shock': 8097, 'today': 9157, 'begin': 873, 'experi': 3261, 'haunt': 4270, 'rest': 7544, 'tortur': 9222, 'conscienc': 2222, 'worri': 9894, 'bodi': 1016, 'river': 7630, 'live': 5371, 'histori': 4445, 'smart': 8243, 'brilliant': 1601, 'jon': 4923, 'voight': 9526, 'burt': 1666, 'magnific': 5528, 'base': 634, 'novel': 6521, 'lover': 5477, 'ever time': 3193, 'about year': 12, 'rape scene': 7332, 'movi today': 6107, 'realli movi': 7393, 'movi realli': 6078, 'way thing': 9678, 'end end': 3001, 'end movi': 3009, 'br act': 1086, 'act also': 51, 'jon voight': 4924, 'movi movi': 6052, 'movi base': 5971, 'see movi': 7961, 'br br act': 1120, 'deal': 2485, 'age': 178, 'encount': 2990, 'potenti': 7098, 'format': 3796, 'suggest': 8701, 'health': 4346, 'face': 3300, 'trauma': 9263, 'disease': 2691, 'primarili': 7157, 'patient': 6788, 'heart': 4350, 'struggle': 8647, 'portray': 7083, 'command': 2138, 'movi ani': 5964, 'plot line': 7023, 'admit': 142, 'scarecrow': 7818, 'tone': 9177, 'mayb': 5686, 'much': 6185, 'cheesy': 1943, 'beautiful': 831, 'factor': 3315, 'sever': 8036, 'view': 9494, 'sheriff': 8085, 'drunk': 2846, 'boyfriend': 1085, 'yes': 9964, 'quit bit': 7291, 'not mention': 6438, 'here get': 4399, 'get end': 3959, 'budget movie': 1642, 'movie veri': 6171, 'thug': 9056, 'kill': 5098, 'doctor': 2752, 'realiz': 7379, 'plague': 6975, 'nasti': 6251, 'find': 3701, 'contact': 2235, 'treat': 9271, 'immediately': 4639, 'disast': 2681, 'oddly': 6571, 'seri': 8012, 'lectur': 5240, 'fact': 3305, 'peopl': 6823, 'ill': 4621, 'grotesqu': 4158, 'fever': 3430, 'bleed': 988, 'vomit': 9529, 'blood': 1000, 'enorm': 3053, 'understand': 9374, 'go': 4062, 'far': 3351, 'feder': 3400, 'govern': 4113, 'involv': 4796, 'control': 2252, 'level': 5276, 'believ': 889, 'acting': 80, 'richard': 7599, 'widmark': 9794, 'paul': 6796, 'dougla': 2789, 'respectively': 7541, 'chief': 1958, 'menac': 5736, 'jack': 4827, 'palanc': 6724, 'walter': 9555, 'mostel': 5934, 'scari': 7820, 'typic': 9360, 'earli': 2894, 'sort': 8394, 'evil': 3217, 'despit': 2588, 'detail': 2597, 'wrap': 9906, 'littl': 5359, 'man also': 5584, 'time find': 9092, 'histori film': 4446, 'film realli': 3623, 'realli not': 7396, 'not do': 6387, 'do job': 2738, 'have show': 4322, 'also lot': 271, 'have much': 4307, 'much much': 6191, 'film actor': 3450, 'richard widmark': 7600, 'actor also': 99, 'also actor': 257, 'however film': 4559, 'still go': 8551, 'well time': 9740, 'br despit': 1346, 'not get': 6413, 'littl too': 5368, 'film well': 3682, 'br br despit': 1161, 'screenplay': 7899, 'book': 1037, 'lucill': 5486, 'ball': 612, 'mistak': 5848, 'biopic': 954, 'rang': 7324, 'write': 9916, 'list': 5350, 'jr': 4937, 'tri': 9277, 'aw': 552, 'sloppi': 8236, 'movi never': 6057, 'never book': 6291, 'never so': 6312, 'not be': 6370, 'be anyon': 668, 'film tri': 3669, 'moment': 5876, 'decision': 2509, 'danger': 2450, 'crimin': 2362, 'dumb': 2858, 'amount': 317, 'money': 5888, 'bank': 618, 'whi': 9767, 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'amazing': 307, 'onc while': 6602, 'amaz film': 306, 'film be': 3467, 'be world': 817, 'money make': 5894, 'ago': 183, 'title': 9152, 'candi': 1721, 'credit': 2352, 'entri': 3081, 'name': 6243, 'crime': 2360, 'someth': 8361, 'bell': 898, 'click': 2042, 'read': 7367, 'pretti': 7145, 'rather': 7343, 'riff': 7609, 'hitchcock': 4453, 'formula': 3797, 'ident': 4610, 'amongst': 315, 'coupl': 2303, 'dog': 2765, 'vacat': 9410, 'europ': 3114, 'return': 7566, 'reward': 7591, 'mix': 5858, 'mad': 5513, 'feature': 3399, 'eugen': 3113, 'film credit': 3492, 'pretti well': 7147, 'despit fact': 2590, 'fact not': 3313, 'not mean': 6437, 'movi cast': 5986, 'onli find': 6619, 'br kind': 1402, 'star movi': 8501, 'br br kind': 1207, 'hit': 4451, 'soon': 8381, 'blockbuster': 996, 'loser': 5425, 'sweet': 8764, 'sacrific': 7744, 'hero': 4411, 'ladi': 5177, 'gandhi': 3897, 'tag': 8788, 'attitud': 520, 'thought': 9041, 'henc': 4380, 'crass': 2333, 'stupid': 8663, 'funni': 3869, 'hair': 4206, 'cant': 1728, 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'memor': 5733, 'lesson': 5259, 'stun': 8661, 'climax': 2049, 'keep': 5063, 'nature': 6257, 'rivet': 7631, 'lend': 5250, 'possibl': 7092, 'outstand': 6691, 'turmoil': 9326, 'beneath': 908, 'exterior': 3284, 'deepli': 2518, 'capabl': 1731, 'joey': 4906, 'walsh': 9553, 'jay': 4859, 'george': 3939, 'maci': 5510, 'moran': 5919, 'direct': 2649, 'future': 3877, 'perfection': 6855, 'miss': 5845, 'charact studi': 1903, 'person life': 6890, 'man time': 5599, 'book be': 1038, 'time not': 9107, 'film keep': 3554, 'charact be': 1872, 'perform here': 6865, 'play film': 6992, 'be one': 757, 'movi not': 6059, 'not want': 6503, 'domino': 2772, 'question': 7282, 'thriller': 9048, 'convolut': 2263, 'halfway': 4211, 'throw': 9052, 'arm': 433, 'scream': 7890, 'gene': 3922, 'stanley': 8493, 'mess': 5748, 'ever be': 3175, 'onli be': 6617, 'happen': 4231, 'wash': 9591, 'comeback': 2124, 'reunion': 7569, 'tour': 9227, 'strang': 8627, 'fruit': 3849, 'toni': 9180, 'rea': 7363, 'machin': 5508, 'promot': 7210, 'festival': 3428, 'festiv': 3427, 'wave': 9645, 'search': 7922, 'replac': 7514, 'keith': 5075, 'timothi': 9142, 'rocker': 7658, 'mansion': 5623, 'sell': 7987, 'fortun': 3801, 'brian': 1589, 'try': 9319, 'abandon': 0, 'manag': 5602, 'label': 5168, 'club': 2067, 'europe': 3116, 'conflict': 2213, 'chanc': 1854, 'tap': 8817, 'ii': 4619, 'becom': 859, 'relationship': 7475, 'struggl': 8646, 'work class': 9865, 'again so': 176, 'scene not': 7846, 'not kind': 6425, 'film start': 3647, 'br still': 1510, 'person film': 6888, 'film work': 3685, 'br br still': 1295, 'disturb': 2717, 'depict': 2562, 'truth': 9317, 'kid': 5089, 'techniqu': 8841, 'la': 5166, 'blair': 978, 'witch': 9822, 'ben': 904, 'succeed': 8688, 'issu': 4813, 'exact': 3222, 'hate': 4267, 'carri': 1771, 'massacr': 5657, 'zero': 9991, 'power': 7107, 'matter': 5678, 'film not': 3590, 'blair witch': 979, 'be lot': 739, 'lot peopl': 5439, 'part just': 6758, 'just believ': 4964, 'not script': 6473, 'venom': 9442, 'bloodi': 1003, 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'lot br br': 5432, 'crush': 2387, 'motif': 5940, 'thief': 8975, 'metaphor': 5756, 'juvenil': 5048, 'accus': 41, 'confin': 2211, 'sorry': 8393, 'sort thing': 8397, 'now film': 6530, 'have watch': 4330, 'br have': 1389, 'have interest': 4295, 'there too': 8964, 'too time': 9210, 'centuri': 1837, 'fox': 3810, 'ingredi': 4703, 'determin': 2600, 'essenc': 3105, 'stress': 8637, 'circumst': 2012, 'exagger': 3224, 'awhile': 567, 'relat': 7474, 'appeal': 410, 'roach': 7634, 'exclus': 3239, 'finish': 3713, 'be far': 712, 'far be': 3353, 'be work': 816, 'work as': 9860, 'humor film': 4579, 'realli be': 7382, 'be today': 803, 'point be': 7046, 'film art': 3460, 'way not': 9668, 'go make': 4077, 'cathol': 1814, 'church': 1999, 'sin': 8177, 'individu': 4687, 'often': 6582, 'therebi': 8966, 'deni': 2549, 'entranc': 3080, 'redemption': 7451, 'wander': 9558, 'anti': 368, 'spiritu': 8444, 'alex': 215, 'ledger': 5241, 'priest': 7155, 'knowledge': 5147, 'mentor': 5740, 'send': 7991, 'underworld': 9378, 'princip': 7162, 'burst': 1665, 'despair': 2585, 'notabl': 6512, 'rule': 7724, 'attraction': 524, 'forth': 3799, 'arc': 422, 'gap': 3900, 'structur': 8644, 'truli': 9313, 'antagonist': 365, 'forc': 3783, 'combin': 2115, 'subtl': 8682, 'orchestr': 6649, 'decept': 2504, 'remain': 7488, 'engag': 3038, 'function': 3866, 'sheer': 8077, 'prevent': 7150, 'cathol church': 1815, 'be thing': 800, 'be perform': 762, 'perform film': 6864, 'br plot': 1466, 'back forth': 583, 'scene be': 7825, 'be also': 666, 'fact never': 3312, 'end film': 3004, 'time film': 9091, 'even begin': 3123, 'film charact': 3485, 'someth br': 8363, 'br mention': 1421, 'be veri': 808, 'peopl be': 6824, 'be turn': 805, 'turn movi': 9332, 'movi even': 6003, 'still film': 8547, 'dvd be': 2880, 'recommend film': 7438, 'peopl think': 6843, 'br br plot': 1254, 'br br mention': 1223, 'memory': 5735, 'realist': 7375, 'buff': 1643, 'enjoy movi': 3049, 'br fun': 1377, 'fun watch': 3865, 'br br fun': 1186, 'jami': 4846, 'kennedi': 5079, 'prove': 7229, 'darker': 2456, 'ever movi': 3187, 'ever so': 3192, 'interest look': 4760, 'watch movi': 9620, 'movi ever movi': 6006, 'kidman': 5096, 'vehicle': 9438, 'element': 2953, 'chaplin': 1866, 'romant': 7689, 'implaus': 4646, 'baby': 572, 'weird': 9701, 'killer': 5105, 'romant comedi': 7690, 'movi enjoy': 6001, 'be killer': 732, 'home video': 4481, 'reign': 7470, 'sandler': 7772, 'don': 2773, 'tyler': 9356, 'sutherland': 8760, 'robert': 7644, 'dillon': 2640, 'allen': 228, 'affect': 157, 'unit': 9387, 'colleg': 2102, 'roommat': 7699, 'wealth': 9684, 'alli': 230, 'genuin': 3937, 'solut': 8349, 'donald sutherland': 2776, 'do work': 2750, 'purpl': 7259, 'cigarett': 2001, 'conversation': 2256, 'beforehand': 870, 'particip': 6769, 'ani film': 346, 'like movie': 5325, 'becaus film': 842, 'peopl just': 6832, 'just stand': 5023, 'still time': 8562, 'understand br': 9375, 'star film': 8500, 'film look': 3565, 'forward see': 3806, 'time have': 9096, 'have sex': 4321, 'sex scene': 8042, 'look forward see': 5404, 'angel': 333, 'mum': 6198, 'br sort': 1502, 'even not': 3147, 'annoy': 359, 'unfunni': 9383, 'romano': 7688, 'gag': 3886, 'vet': 9479, 'loop': 5417, 'fbi': 3393, 'destroy': 2593, 'trace': 9233, 'duti': 2877, 'mayhem': 5693, 'ensu': 3064, 'straight': 8623, 'settl': 8033, 'chris': 1981, 'alarm': 208, 'slapstick': 8216, 'snl': 8258, 'reli': 7482, 'routine': 7713, 'torture': 9223, 'mafia': 5521, 'tick': 9062, 'plenti': 7008, 'screenwrit': 7900, 'penn': 6821, 'peter': 6902, 'falk': 3327, 'whi film': 9771, 'so well': 8333, 'then film': 8923, 'say br': 7801, 'tri do': 9280, 'right so': 7617, 'so life': 8297, 'lead actor': 5228, 'minut film': 5820, 'have movi': 4305, 'movi just': 6036, 'time write': 9134, 'watch even': 9612, 'peter falk': 6903, 'say br br': 7802, 'react': 7365, 'accord': 36, 'voice': 9524, 'warhol': 9581, 'descend': 2572, 'exploit': 3272, 'max': 5685, 'value': 9420, 'portrait': 7082, 'genius': 3930, 'ourselv': 6678, 'just wonder': 5042, 'be 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'sympathet': 8775, 'monster': 5904, 'hint': 4439, 'terror': 8880, 'film especi': 3512, 'have br': 4277, 'br charact': 1335, 'probabl not': 7173, 'have br br': 4278, 'br br charact': 1151, 'br film be': 1370, 'dancer': 2446, 'bridg': 1592, 'excit': 3237, 'film alway': 3456, 'music danc': 6214, 'damag': 2432, 'garner': 3910, 'market': 5639, 'weaver': 9690, 'claud': 2029, 'darn': 2458, 'successfully': 8690, 'outlaw': 6685, 'saloon': 7759, 'eastwood': 2906, 'spent': 8431, 'territori': 8878, 'lock': 5379, 'transport': 9259, 'togeth': 9162, 'heist': 4367, 'protagonist': 7224, 'method': 5758, 'break': 1575, 'gold': 4093, 'gut': 4186, 'thirti': 9033, 'chorus': 1978, 'alway get': 297, 'well film': 9717, 'br role': 1485, 'br here': 1390, 'movi goe': 6025, 'just too': 5031, 'not thing': 6493, 'film lot': 3566, 'film mayb': 3575, 'better br': 932, 'br br role': 1273, 'br br here': 1198, 'br br just': 1205, 'ah': 189, 'personally': 6895, 'tremend': 9275, 'dude': 2853, 'walken': 9549, 'cute': 2416, 'pleasure': 7007, 'country': 2297, 'seriously': 8020, 'clichéd': 2040, 'sentiment': 8000, 'pow': 7104, 'symbol': 8772, 'debt': 2498, 'rebel': 7420, 'revolut': 7587, 'presid': 7136, 'columbia': 2109, 'execut': 3243, 'president': 7137, 'travel': 9265, 'assist': 494, 'vietnam': 9493, 'miser': 5837, 'plane': 6978, 'open': 6631, 'okay': 6589, 'fool': 3776, 'compos': 2184, 'add': 134, 'heroic': 4412, 'goal': 4084, 'mission': 5847, 'squad': 8469, 'coher': 2088, 'plausibl': 6987, 'outrag': 6688, 'nation': 6253, 'gunfight': 4182, 'soundtrack': 8403, 'joan': 4895, 'charact name': 1892, 'christoph walken': 1995, 'becaus there': 853, 'motion picture': 5943, 'too seriously': 9207, 'action sequenc': 92, 'charact movie': 1891, 'br okay': 1451, 'let not': 5270, 'quit time': 7293, 'even have': 3138, 'not expect': 6401, 'br br okay': 1241, 'arch': 423, 'march': 5629, 'teacher': 8834, 'experience': 3263, 'link': 5345, 'print': 7164, 'size': 8204, 'restor': 7553, 'cultur': 2399, 'agenc': 179, 'import': 4649, 'gasp': 3912, 'valley': 9417, 'antonioni': 374, 'wake': 9546, 'inde': 4677, 'leonard': 5256, 'romeo': 7692, 'her': 4386, 'everything': 3212, 'daylight': 2478, 'hippi': 4442, 'insid': 4719, 'environment': 3083, 'glimps': 4054, 'photo': 6921, 'restaurant': 7552, 'that': 8897, 'peace': 6809, 'too too': 9211, 'let face': 5263, 'br time': 1527, 'br year': 1556, 'work art': 9859, 'keep thing': 5071, 'place br': 6967, 'feel film': 3407, 'die br': 2623, 'let go': 5265, 'go br': 4069, 'time so': 9119, 'br see': 1492, 'movi show': 6089, 'be screen': 781, 'br so': 1499, 'so still': 8323, 'br br time': 1308, 'br br year': 1330, 'die br br': 2624, 'br br then': 1304, 'br br so': 1286, 'moron': 5930, 'advis': 155, 'acid': 46, 'info': 4699, 'defend': 2522, 'paper': 6733, 'lion': 5346, 'again make': 173, 'make think': 5566, 'be take': 796, 'forti': 3800, 'fault': 3383, 'violence': 9511, 'unlik': 9390, 'clockwork': 2056, 'sum': 8707, 'walker': 9550, 'desire': 2584, 'bedroom': 861, 'mere': 5743, 'leg': 5244, 'challeng': 1848, 'themselv': 8914, 'aim': 195, 'remov': 7499, 'nobl': 6336, 'joy': 4935, 'carol': 1765, 'reed': 7455, 'idol': 4615, 'powel': 7105, 'sidney': 8154, 'lumet': 5494, 'glory': 4057, 'celluloid': 1830, 'film feel': 3522, 'minut so': 5825, 'not actor': 6362, 'writer director': 9919, 'be bit': 678, 'br think': 1526, 'man film': 5589, 'film far': 3520, 'sidney lumet': 8155, 'br br think': 1307, 'bett': 929, 'davi': 2463, 'flop': 3757, 'variat': 9430, 'distinct': 2709, 'phone': 6918, 'misunderstood': 5853, 'bett davi': 930, 'be act': 660, 'behaviour': 883, 'noth': 6515, 'thing realli': 9004, 'not stori': 6486, 'stori so': 8599, 'so charact': 8273, 'charact so': 1900, 'warner': 9585, 'stanwyck': 8494, 'wilder': 9800, 'lili': 5328, 'daughter': 2461, 'owner': 6705, 'steel': 8525, 'sleep': 8227, 'ladder': 5176, 'blaze': 986, 'amor': 316, 'seduct': 7936, 'wayn': 9682, 'third': 9032, 'fund': 3867, 'bond': 1027, 'friendship': 3840, 'immigr': 4640, 'philosophi': 6916, 'film 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1315, 'br br seri': 1280, 'busi': 1672, 'harri': 4253, 'godfather': 4089, 'spoof': 8458, 'goon': 4105, 'parody': 6749, 'be budget': 683, 'not realli': 6466, 'charact br': 1873, 'tell not': 8858, 'movie be': 6130, 'also see': 282, 'actor film': 105, 'action br': 85, 'support cast': 8731, 'well cast': 9712, 'movi book': 5979, 'movie then': 6167, 'then end': 8921, 'movi rate': 6075, 'charact br br': 1874, 'wretch': 9912, 'holi': 4465, 'law': 5218, 'degener': 2527, 'sub': 8671, 'purchas': 7256, 'ratio': 7353, 'demon': 2547, 'chiller': 1963, 'exec': 3242, 'cater': 1812, 'travesti': 9266, 'masquerad': 5655, 'sub plot': 8672, 'tv movi': 9338, 'produc movi': 7185, 'give away': 4030, 'death scene': 2494, 'ever screen': 3190, 'disturbing': 2718, 'rapist': 7333, 'tabl': 8783, 'confess': 2209, 'maybe': 5692, 'fawcett': 3391, 'russo': 7738, 'alfr': 217, 'stuf': 8656, 'arriv': 444, 'therefore': 8968, 'polic': 7062, 'faint': 3322, 'grip': 4155, 'anchor': 324, 'way home': 9660, 'be man': 742, 'man 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'baptist': 620, 'contempl': 2237, 'rhythm': 7597, 'photographi': 6923, 'norman': 6354, 'fisher': 3725, 'boxer': 1078, 'brad': 1559, 'pitt': 6961, 'alcohol': 212, 'appli': 414, 'worm': 9893, 'bait': 606, 'refus': 7462, 'wait': 9541, 'plate': 6984, 'jessi': 4880, 'burn': 1664, 'propos': 7221, 'chicago': 1955, 'narrator': 6250, 'producer': 7186, 'hundr': 4582, 'technolog': 8843, 'memori': 5734, 'never tire': 6313, 'movi too': 6108, 'type movi': 9359, 'act scene': 71, 'brad pitt': 1560, 'back home': 584, 'decid go': 2506, 'not stop': 6485, 'chanc see': 1856, 'life death': 5296, 'curs': 2407, 'toronto': 9221, 'distribution': 2714, 'shaun': 8070, 'press': 7138, 'devot': 2610, 'pulp': 7245, 'fido': 3434, 'ann': 354, 'moss': 5932, 'dylan': 2889, 'blake': 981, 'nelson': 6276, 'testament': 8884, 'brillianc': 1599, 'implic': 4648, 'accident': 32, 'servant': 8023, 'butler': 1680, 'labor': 5169, 'pet': 6900, 'was': 9590, 'poke': 7057, 'bitter': 969, 'lake': 5179, 'rebelli': 7421, 'drift': 2829, 'deadpan': 2483, 'satire': 7787, 'drill': 2831, 'film festiv': 3523, 'time get': 9094, 'case br': 1777, 'br ever': 1360, 'be dure': 700, 'period br': 6877, 'script film': 7909, 'time be': 9077, 'take look': 8798, 'start get': 8512, 'case br br': 1778, 'br br ever': 1175, 'period br br': 6878, 'cold': 2093, 'silly': 8164, 'intelligent': 4749, 'revenge': 7575, 'jaw': 4857, 'realism': 7374, 'make be': 5535, 'so say': 8316, 'go ahead': 4063, 'exit': 3249, 'so never': 8306, 'br however': 1394, 'then so': 8937, 'br sum': 1513, 'war movi': 9577, 'br br however': 1200, 'br br sum': 1298, 'christma': 1990, 'scrooge': 7917, 'surpass': 8744, 'honesti': 4491, 'tribut': 9295, 'gift': 4013, 'trade': 9237, 'utter': 9409, 'express': 3279, 'maintain': 5532, 'integr': 4745, 'perhaps': 6874, 'alec': 213, 'carter': 1772, 'sincer': 8184, 'qualiti': 7274, 'mrs': 6181, 'anthoni': 367, 'roger': 7664, 'narrat': 6248, 'forev': 3788, 'schedul': 7861, 'holiday': 4466, 'time around': 9075, 'make seem': 5559, 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6333, 'acquir': 49, 'br look': 1412, 'look way': 5415, 'idea not': 4608, 'place not': 6971, 'so here': 8291, 'be script': 782, 'script have': 7910, 'be point': 767, 'well see': 9734, 'know be': 5132, 'even so': 3157, 'so think': 8329, 'think film': 9019, 'film heart': 3539, 'quit so': 7292, 'br br look': 1215, 'superman': 8723, 'mighti': 5784, 'rambo': 7316, 'matrix': 5676, 'jacki': 4833, 'chan': 1853, 'jet': 4885, 'li': 5281, 'mask': 5653, 'choreograph': 1975, 'officer': 6580, 'department': 2559, 'jacki chan': 4834, 'bruce lee': 1624, 'jet li': 4886, 'premis film': 7126, 'film doe': 3503, 'be be': 675, 'be do': 699, 'watch so': 9631, 'br art': 1102, 'art film': 449, 'know film': 5138, 'lot lot': 5435, 'lot action': 5429, 'flock': 3754, 'dane': 2449, 'synopsi': 8779, 'onlin': 6629, 'dan': 2439, 'minute': 5827, 'badly': 602, 'becaus stori': 852, 'befor movi': 866, 'do so': 2746, 'script so': 7914, 'so make': 8301, 'believ charact': 891, 'realli feel': 7386, 'castl': 1803, 'sky': 8212, 'miyazaki': 5860, 'storytel': 8621, 'translat': 9256, 'movi feel': 6014, 'again just': 172, 'be now': 756, 'now here': 6533, 'book br': 1039, 'tast': 8824, 'steam': 8524, 'singl': 8188, 'redeem': 7448, 'anywher': 400, 'penni': 6822, 'associ': 496, 'slater': 8222, 'hapless': 4230, 'masterpiec': 5664, 'movi complet': 5990, 'complet wast': 2178, 'movi yet': 6126, 'not singl': 6478, 'br onli': 1454, 'posit review': 7089, 'tell film': 8857, 'film one': 3600, 'film let': 3559, 'film script': 3632, 'complet wast time': 2179, 'wast time br': 9597, 'br br onli': 1244, 'walt': 9554, 'roy': 7716, 'atlantis': 504, 'ideal': 4609, 'whack': 9754, 'till': 9068, 'hammi': 4220, 'steal': 8523, 'recal': 7423, 'forgett': 3791, 'interest not': 4763, 'thank god': 8895, 'charact actor': 1869, 'satir': 7786, 'magic': 5525, 'christ': 1983, 'br view': 1539, 'be stori': 794, 'br br view': 1319, 'antonio': 373, 'vibe': 9482, 'journalist': 4933, 'edgar': 2916, 'spend': 8427, 'poe': 7040, 'th': 8889, 'me': 5702, 'crypt': 2390, 'eeri': 2926, 'spend night': 8429, 'th film': 8891, 'intrigu': 4783, 'smell': 8245, 'textur': 8888, 'cinematograph': 2008, 'orang': 6648, 'glow': 4061, 'plastic': 6983, 'perspect': 6896, 'notion': 6519, 'himself': 4434, 'grandmoth': 4130, 'situation': 8202, 'cook': 2264, 'me br': 5703, 'himself br': 4435, 'br someon': 1500, 'end just': 3007, 'well watch': 9744, 'me br br': 5704, 'himself br br': 4436, 'br br someon': 1287, 'obtain': 6563, 'pleas': 7002, 'bottom': 1066, 'description': 2578, 'cbs': 1823, 'christmas': 1992, 'depression': 2564, 'hospit': 4531, 'shut': 8147, 'hank': 4228, 'russ': 7733, 'slip': 8234, 'explan': 3269, 'public': 7241, 'very': 9477, 'claus': 2030, 'suit': 8704, 'advice': 154, 'copy': 2272, 'com': 2111, 'copi film': 2271, 'very veri': 9478, 'now again': 6526, 'plot even': 7019, 'ireland': 4801, 'religi': 7485, 'stray': 8630, 'path': 6784, 'courtesi': 2316, 'cannib': 1725, 'clan': 2023, 'ton': 9176, 'nuditi': 6547, 'breed': 1585, 'ginger': 4018, 'slaughter': 8223, 'enhanc': 3044, 'off': 6574, 'spit': 8445, 'promis': 7208, 'downhill': 2800, 'beg': 872, 'form': 3795, 'gari': 3908, 'convent': 2255, 'knife': 5127, 'ram': 7314, 'flesh': 3744, 'jameson': 4845, 'breast': 1581, 'taylor': 8831, 'hay': 4336, 'nake': 6242, 'gori': 4109, 'worthwhile': 9903, 'eventu': 3171, 'concern': 2197, 'despit be': 2589, 'br budget': 1332, 'budget horror': 1640, 'rest film': 7547, 'thing start': 9008, 'amount time': 318, 'time wast': 9129, 'horror film': 4524, 'then just': 8928, 'film never': 3587, 'never get': 6299, 'get guy': 3967, 'guy get': 4190, 'rate br': 7339, 'have as': 4274, 'br br budget': 1148, 'rate br br': 7340, 'as well have': 472, 'saw': 7798, 'seller': 7988, 'lame': 5180, 'pink': 6953, 'fine': 3711, 'excus': 3241, 'peter seller': 6905, 'be there': 799, 'never have': 6303, 'produc film': 7184, 'rendit': 7502, 'myth': 6237, 'singing': 8187, 'instrument': 4742, 'bust': 1675, 'disney movi': 2701, 'definit not': 2525, 'not film': 6406, 'savag': 7790, 'trust': 9316, 'moments': 5881, 'reflect': 7460, 'br boy': 1119, 'moments br': 5882, 'br fact': 1365, 'fact film': 3309, 'film sever': 3636, 'br br boy': 1146, 'moments br br': 5883, 'br br also': 1127, 'br br fact': 1178, 'miller': 5794, 'superstar': 8726, 'awkward': 568, 'conclusion': 2201, 'sinc not': 8182, 'still not': 8559, 'disagre': 2676, 'bibl': 940, 'chip': 1966, 'grain': 4125, 'rice': 7598, 'runner': 7731, 'beast': 825, 'everyon see': 3206, 'see version': 7973, 'version be': 9470, 'still see': 8560, 'truck': 9312, 'sign': 8157, 'suspense': 8756, 'br base': 1110, 'group friend': 4161, 'act so': 73, 'budget film': 1639, 'flaw': 3738, 'discov': 2688, 'balanc': 609, 'remak': 7490, 'them': 8907, 'aforement': 160, 'teen': 8845, 'target': 8821, 'brave': 1570, 'plot so': 7031, 'even br': 3125, 'them br': 8908, 'br lack': 1404, 'night br': 6326, 'br script': 1489, 'script br': 7905, 'even show': 3156, 'save money': 7795, 'money br': 5891, 'even br br': 3126, 'them br 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3118, 'aspir': 486, 'fulfil': 3854, 'dare': 2454, 'hesit': 4417, 'disciplin': 2685, 'thelma': 8906, 'contrast': 2249, 'perspective': 6897, 'crazi': 2339, 'wear': 9687, 'no': 6334, 'jackson': 4836, 'coleman': 2095, 'characteris': 1913, 'reson': 7537, 'mainstream': 5531, 'wherea': 9765, 'address': 138, 'sassi': 7784, 'jump': 4951, 'shark': 8066, 'accid': 31, 'mi': 5762, 'yet br': 9969, 'tri make': 9287, 'love wife': 5474, 'br kid': 1401, 'love relationship': 5465, 'brother sister': 1621, 'extrem well': 3288, 'show show': 8136, 'show be': 8120, 'br show': 1496, 'br mi': 1423, 'mi rating': 5765, 'yet br br': 9970, 'br br fan': 1179, 'br br kid': 1206, 'br br show': 1283, 'br br mi': 1224, 'br mi rating': 1425, 'stunt': 8662, 'fantast': 3349, 'flawless': 3740, 'listen': 5352, 'fight scene': 3439, 'be charact': 688, 'movi lot': 6043, 'bias': 939, 'departur': 2560, 'adventure': 151, 'just keep': 4990, 'recommend anyon': 7434, 'updat': 9395, 'aunt': 535, 'franc': 3813, 'bride': 1591, 'bed': 860, 'build': 1646, 'guess be': 4170, 'be sort': 791, 'movi minut': 6051, 'woman be': 9832, 'get hand': 3968, 'not much': 6445, 'yet not': 9973, 'not know': 6426, 'hat': 4266, 'service': 8025, 'awful': 565, 'ta': 8782, 'actor not': 112, 'have film': 4288, 'film littl': 3563, 'coupl hour': 2304, 'hour life': 4542, 'life watch': 5310, 'be look': 738, 'look not': 5410, 'not yet': 6511, 'yet just': 9972, 'just expect': 4976, 'otherwis': 6676, 'recogniz': 7432, 'fortunately': 3802, 'years': 9959, 'bar': 621, 'correct': 2283, 'murderer': 6203, 'relev': 7481, 'shakespear': 8055, 'revel': 7572, 'years br': 9960, 'year film': 9946, 'film focus': 3528, 'play charact': 6991, 'br documentari': 1351, 'documentari film': 2755, 'film book': 3476, 'years br br': 9961, 'br movi not': 1433, 'drama br br': 2815, 'br br documentari': 1166, 'cole': 2094, 'grave': 4137, 'pad': 6715, 'board': 1011, 'rhyme': 7596, 'forget': 3790, 'boring': 1059, 'pointless': 7055, 'skip': 8208, 'late night': 5198, 'also br': 260, 'br start': 1509, 'fall apart': 3329, 'minut long': 5822, 'easili be': 2902, 'sound br': 8401, 'corner': 2277, 'boot': 1050, 'stewart': 8537, 'novak': 6520, 'bicker': 941, 'letter': 5275, 'morgan': 5926, 'ambiti': 311, 'tracy': 9236, 'clerk': 2036, 'dismiss': 2698, 'clara': 2024, 'invit': 4795, 'snow': 8260, 'winter': 9815, 'glad': 4045, 'asid': 477, 'descript': 2577, 'extreme': 3289, 'perfectly': 6856, 'whenev': 9764, 'especially': 3103, 'earnest': 2898, 'broken': 1612, 'sweetheart': 8765, 'breakdown': 1578, 'lubitsch': 5483, 'creation': 2345, 'regist': 7466, 'chose': 1979, 'mail': 5530, 'harm': 4251, 'charming': 1927, 'comedi ever': 2128, 'ever just': 3184, 'love story': 5471, 'ever happen': 3182, 'get be': 3948, 'co work': 2075, 'veri beginning': 9448, 'stori film': 8586, 'film support': 3655, 'support charact': 8732, 'christma eve': 1991, 'even charact': 3128, 'tell br': 8855, 'br asid': 1105, 'thing film': 8988, 'wait see': 9544, 'also way': 288, 'do even': 2734, 'film scene': 3630, 'turn perform': 9333, 'br doe': 1352, 'doe film': 2760, 'story charact': 8613, 'as possibl': 466, 'help make': 4378, 'make even': 5540, 'be not': 754, 'film peopl': 3605, 'so have': 8290, 'film thing': 3663, 'film not film': 3593, 'br br doe': 1167, 'evening': 3168, 'intend': 4750, 'manag be': 5603, 'so movi': 8303, 'movie never': 6153, 'never ani': 6287, 'ani actor': 342, 'care happen': 1751, 'feel be': 3403, 'hunt': 4586, 'bigfoot': 942, 'pacif': 6709, 'stereotype': 8532, 'sasquatch': 7783, 'rifl': 7610, 'hope see': 4508, 'see lot': 7960, 'not like': 6429, 'just enjoy': 4973, 'get laugh': 3980, 'johnson': 4916, 'monkey': 5901, 'squeez': 8471, 'asham': 474, 'spend time': 8430, 'ever br': 3176, 'even make': 3143, 'minut life': 5821, 'everyon involv': 3205, 'ever br br': 3177, 'vanilla': 9428, 'logic': 5382, 'leader': 5230, 'hbo': 4339, 'butt': 1681, 'chemistry': 1946, 'album': 211, 'fade': 3318, 'drag': 2809, 'rant': 7329, 'setup': 8034, 'sometimes': 8371, 'hammer': 4219, 'phase': 6910, 'good': 4099, 'ripoff': 7623, 'heard': 4349, 'manager': 5606, 'ignor': 4618, 'hop': 4503, 'exist': 3247, 'be guy': 722, 'film then': 3661, 'then scene': 8934, 'br coupl': 1341, 'coupl year': 2306, 'too fast': 9191, 'realli work': 7403, 'stori then': 8602, 'then go': 8926, 'back watch': 592, 'yet so': 9975, 'br go': 1382, 'save time': 7797, 'br find': 1373, 'think not': 9025, 'film much': 3583, 'hip hop': 4441, 'thing even': 8986, 'br br coupl': 1157, 'br br go': 1191, 'br br find': 1183, 'dress': 2824, 'ie': 4616, 'jersey': 4877, 'giant': 4010, 'sf': 8047, 'bowl': 1074, 'africa': 161, 'further': 3874, 'communiti': 2156, 'coast': 2077, 'hood': 4498, 'vs': 9537, 'act way': 78, 'veri differ': 9450, 'hyde': 4593, 'glass': 4050, 'pervert': 6899, 'episode': 3088, 'playboy': 6999, 'girlfriend': 4028, 'veteran': 9480, 'donna': 2778, 'hmm': 4456, 'basement': 639, 'show time': 8139, 'want get': 9564, 'doe anyon': 2759, 'then come': 8920, 'mini': 5808, 'endur': 3031, 'exercis': 3245, 'tribe': 9294, 'opera': 6634, 'ability': 5, 'prepar': 7129, 'rush': 7732, 'get go': 3966, 'live life': 5372, 'rather br': 7345, 'well act': 9705, 'so scene': 8317, 'scene so': 7850, 'stage product': 8479, 'show have': 8128, 'rather br br': 7346, 'thi': 8971, 'vain': 9414, 'woodi': 9850, 'thi movi': 8973, 'movi br': 5981, 'star br': 8497, 'plot be': 7012, 'woodi allen': 9851, 'see film': 7952, 'movi br br': 5982, 'star br br': 8498, 'offbeat': 6575, 'acclaim': 33, 'world not': 9889, 'kurosawa': 5162, 'blockbust': 995, 'financi': 3700, 'dramas': 2816, 'uncle': 9369, 'stumbl': 8660, 'sake': 7755, 'salesman': 7757, 'bike': 943, 'shi': 8088, 'erot': 3095, 'margin': 5631, 'scope': 7880, 'meant': 5712, 'force': 3784, 'hollow': 4469, 'rip': 7621, 'cloth': 2064, 'silenc': 8160, 'ironically': 4804, 'painter': 6719, 'alert': 214, 'composit': 2185, 'design': 2582, 'underneath': 9373, 'sword': 8770, 'nonetheless': 6348, 'beard': 824, 'condit': 2204, 'end day': 3000, 'there not': 8962, 'not 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'indiffer': 4686, 'beat': 826, 'em': 2970, 'alison': 224, 'olsen': 6597, 'arrog': 445, 'sophi': 8387, 'culture': 2400, 'needless': 6268, 'stardom': 8506, 'lust': 5500, 'britney': 1607, 'lose': 5424, 'huston': 4592, 'homag': 4476, 'equival': 3092, 'kitchen': 5122, 'branch': 1565, 'part life': 6759, 'br much': 1436, 'br matter': 1418, 'needless say': 6269, 'girl not': 4027, 'make person': 5557, 'anyway br': 397, 'give perform': 4041, 'love interest': 5458, 'also star': 284, 'film complet': 3490, 'back be': 577, 'be again': 664, 'star be': 8496, 'be interest': 730, 'see do': 7949, 'anyway br br': 398, 'basically': 643, 'conceiv': 2194, 'iraq': 4800, 'turd': 9324, 'world war': 9891, 'film kind': 3555, 'type film': 9358, 'not anyth': 6367, 'just look': 4999, 'end realli': 3013, 'rather watch': 7350, 'jackman': 4835, 'mile': 5789, 'be year': 818, 'point br': 7047, 'murder mysteri': 6202, 'be way': 813, 'have so': 4323, 'joke br': 4919, 'point br br': 7048, 'joke br br': 4920, 'spoiler alert': 8455, 'lot not': 5438, 'internet': 4776, 'glanc': 4048, 'cow': 2320, 'chicken': 1957, 'segment': 7982, 'comic': 2137, 'suicide': 8703, 'even know': 3141, 'not show': 6476, 'show even': 8124, 'keep mind': 5070, 'mind not': 5802, 'also time': 286, 'time take': 9121, 'life then': 5307, 'then not': 8931, 'not miss': 6439, 'fact be': 3306, 'be show': 787, 'fort': 3798, 'well enough': 9715, 'enough have': 3059, 'like film': 5322, 'br mind': 1426, 'score br': 7882, 'especi end': 3101, 'so often': 8309, 'br recommend': 1479, 'mind film': 5800, 'br br mind': 1225, 'score br br': 7883, 'br br recommend': 1267, 'pacino': 6711, 'speech': 8422, 'coffin': 2086, 'compliment': 2183, 'remark': 7492, 'interestingly': 4773, 'quit well': 7294, 'br talk': 1518, 'fabul': 3299, 'sirk': 8192, 'hudson': 4566, 'dorothi': 2784, 'malon': 5581, 'stack': 8474, 'sharon': 8067, 'instinct': 4738, 'montag': 5906, 'dimension': 2642, 'scratch': 7888, 'censor': 1832, 'chore': 1974, 'craft': 2326, 'to': 9153, 'rock 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'time just': 9098, 'never happen': 6302, 'br br lot': 1216, 'ol': 6590, 'disbelief': 2683, 'mummi': 6199, 'second': 7926, 'subtleti': 8684, 'credibility': 2350, 'claw': 2031, 'distanc': 2707, 'fright': 3841, 'extraordinari': 3286, 'haunting': 4271, 'non': 6344, 'crowd': 2380, 'mall': 5580, 'slowli': 8238, 'neck': 6264, 'collection': 2100, 'quest': 7281, 'movi fact': 6009, 'movi almost': 5961, 'almost feel': 241, 'find be': 3702, 'film world': 3686, 'have look': 4300, 'br woman': 1548, 'too often': 9203, 'film there': 3662, 'just littl': 4998, 'horror br': 4521, 'film rate': 3621, 'still movi': 8557, 'mayb be': 5687, 'then too': 8943, 'br br woman': 1325, 'horror br br': 4522, 'shining': 8092, 'movi bore': 5980, 'life also': 5290, 'bring back': 1603, 'even now': 3148, 'not work': 6510, 'peopl movi': 6835, 'make horror': 5544, 'movi still': 6094, 'peopl watch': 6845, 'thing peopl': 9003, 'feel br': 3404, 'movi want': 6116, 'want go': 9566, 'time money': 9103, 'still love': 8555, 'do 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2386, 'sinist': 8189, 'insur': 4744, 'verdict': 9444, 'othello': 6672, 'film mani': 3574, 'jane eyre': 4851, 'well make': 9724, 'movi right': 6083, 'not realiz': 6465, 'comment not': 2147, 'br br bi': 1144, 'devoid': 2609, 'split': 8450, 'filler': 3447, 'lol': 5383, 'idea br': 4602, 'film audienc': 3464, 'charact never': 1893, 'hour long': 4543, 'idea br br': 4603, 'take care': 8794, 'seem have': 7981, 'shame film': 8060, 'movi hour': 6032, 'end watch': 3023, 'recently': 7427, 'novelist': 6523, 'see just': 7959, 'br disappoint': 1350, 'charact have': 1884, 'school student': 7868, 'play game': 6993, 'br comment': 1339, 'br ani': 1096, 'jame bond': 4843, 'br br see': 1279, 'film not have': 3594, 'br br disappoint': 1165, 'br br comment': 1155, 'collabor': 2097, 'psychopath': 7240, 'popul': 7075, 'hug': 4567, 'daddi': 2425, 'mon': 5885, 'roller': 7684, 'mcadam': 5696, 'skin': 8207, 'murphi': 6206, 'passabl': 6776, 'terrorist': 8881, 'movi review': 6082, 'guy guy': 4192, 'director br': 2658, 'see guy': 7955, 'save day': 7792, 'be action': 661, 'one get': 6612, 'director br br': 2659, 'goddess': 4087, 'thompson': 9038, 'eh': 2940, 'morn': 5928, 'whi so': 9776, 'so mani': 8302, 'se': 7918, 'let know': 5268, 'baseball': 638, 'do someth': 2747, 'act script': 72, 'harbor': 4243, 'spring': 8467, 'elimin': 2957, 'communism': 2154, 'ration': 7354, 'mustach': 6228, 'spread': 8465, 'germany': 3944, 'fellow': 3419, 'bread': 1574, 'map': 5624, 'clay': 2032, 'berlin': 918, 'year br': 9942, 'look so': 5413, 'stori man': 8595, 'movi tri': 6109, 'movi see': 6087, 'actress not': 126, 'want say': 9568, 'br enough': 1357, 'begin end': 874, 'movi success': 6097, 'part part': 6763, 'br watch movi': 1544, 'br br enough': 1172, 'overdone': 6699, 'strand': 8626, 'slut': 8241, 'sneak': 8255, 'car crash': 1743, 'mother daughter': 5939, 'film girl': 3532, 'kill br': 5099, 'act film': 62, 'bottom barrel': 1067, 'really realli': 7407, 'kill br br': 5100, 'br as far': 1104, 'kate': 5056, 'psychologist': 7239, 'bernard': 919, 'transcend': 9252, 'influence': 4698, 'attitude': 521, 'unfortun': 9380, 'opposite': 6644, 'conserv': 2225, 'glove': 4059, 'hokey': 4461, 'cain': 1698, 'killer br': 5106, 'end there': 3020, 'time director': 9084, 'now year': 6542, 'not follow': 6408, 'too becaus': 9184, 'film concern': 3491, 'not well': 6508, 'hold interest': 4463, 'killer br br': 5107, 'movie ever': 6138, 'end then': 3019, 'movi end': 6000, 'make mind': 5551, 'feel charact': 3406, 'cinematography': 2010, 'da': 2423, 'catherin': 1813, 'hugh': 4568, 'smoke': 8249, 'machine': 5509, 'overwhelm': 6702, 'care ani': 1747, 'ani charact': 345, 'honest say': 4490, 'even see': 3155, 'rather be': 7344, 'be back': 674, 'ki': 5087, 'sholay': 8100, 'mindless': 5804, 'climb': 2050, 'pistol': 6957, 'hindi': 4437, 'raj': 7312, 'brood': 1615, 'amitabh': 314, 'wrist': 9914, 'elev': 2956, 'word describ': 9853, 'even tri': 3164, 'movi heart': 6029, 'film fan': 3519, 'be origin': 759, 'role film': 7671, 'time screen': 9116, 'wrestler': 9911, 'rampag': 7318, 'wrestl': 9910, 'gentl': 3935, 'bounc': 1068, 'dvd br': 2881, 'fan not': 3343, 'dvd br br': 2882, 'guilti': 4176, 'not plot': 6459, 'br no': 1441, 'too late': 9196, 'joke not': 4921, 'rest br': 7545, 'br br no': 1235, 'dash': 2459, 'premier': 7124, 'volunt': 9528, 'give film': 4037, 'work way': 9878, 'edg seat': 2915, 'stori also': 8580, 'act just': 64, 'well look': 9723, 'well just': 9721, 'br thing movi': 1525, 'movi not be': 6060, 'movi veri well': 6115, 'columbo': 2110, 'patrick': 6791, 'beginning br': 879, 'br excel': 1363, 'beginning br br': 880, 'br br excel': 1177, 'revelation': 7573, 'too end': 9188, 'too well': 9213, 'tri too': 9290, 'not problem': 6461, 'br br much': 1231, 'itali': 4818, 'sunris': 8714, 'grandfather': 4128, 'persuad': 6898, 'sens': 7992, 'lace': 5172, 'lay': 5224, 'conceit': 2193, 'ala': 206, 'poet': 7042, 'sudden': 8694, 'exposit': 3277, 'say so': 7811, 'way there': 9677, 'br meanwhile': 1420, 'see be': 7942, 'there just': 8960, 'just veri': 5036, 'br br meanwhile': 1222, 'just start': 5024, 'end see': 3016, 'film class': 3487, 'pamela': 6728, 'laughabl': 5210, 'tv seri': 9341, 'there also': 8954, 'stori just': 8590, 'year girl': 9947, 'have problem': 4316, 'cave': 1821, 'consist': 2229, 'vacation': 9411, 'sweat': 8763, 'muppet': 6200, 'study': 8655, 'insist': 4722, 'eighti': 2941, 'edge': 2917, 'tri convinc': 9279, 'away br': 559, 'br peopl': 1462, 'tri get': 9283, 'too have': 9194, 'away br br': 560, 'year br br': 9943, 'br br peopl': 1250, 'steven': 8535, 'movi there': 6102, 'so world': 8336, 'foxx': 3811, 'instanc': 4729, 'jami foxx': 4847, 'film person': 3609, 'directing': 2651, 'stori time': 8603, 'piece': 6943, 'way see': 9672, 'belushi': 903, 'prom': 7206, 'hamilton': 4217, 'lifestyl': 5312, 'plot develop': 7016, 'kill movi': 5102, 'end also': 2992, 'film deal': 3496, 'laugh so': 5209, 'elvira': 2969, 'rambl': 7315, 'nowhere': 6544, 'acquaint': 48, 'colin': 2096, 'reliabl': 7483, 'everybodi': 3201, 'holland': 4467, 'charact not': 1894, 'so point': 8313, 'film despit': 3499, 'doe well': 2764, 'like have': 5323, 'time come': 9082, 'so there': 8327, 'littl girl': 5364, 'damsel': 2437, 'distress': 2712, 'flavor': 3737, 'franci': 3817, 'nod': 6338, 'warren': 9588, 'doc': 2751, 'pioneer': 6954, 'electron': 2951, 'less': 5258, 'id': 4599, 'toe': 9161, 'scientif': 7875, 'morbius': 5921, 'recycl': 7447, 'deliber': 2534, 'flood': 3755, 'realize': 7380, 'damsel distress': 2438, 'sex appeal': 8040, 'perhap be': 6872, 'br admit': 1091, 'still give': 8550, 'br br admit': 1125, 'multipl': 6197, 'leather': 5237, 'vignett': 9501, 'celebrity': 1827, 'suav': 8670, 'tini': 9144, 'demeanor': 2544, 'cameron': 1712, 'footage': 3779, 'be play': 765, 'veri job': 9458, 'notice': 6518, 'vari': 9429, 'breathtak': 1584, 'conneri': 2218, 'dustin': 2874, 'hector': 4363, 'hunter': 4587, 'dragon': 2810, 'run away': 7728, 'charact plot': 1896, 'becaus look': 846, 'still get': 8549, 'movi believ': 5977, 'find br': 3703, 'so whi': 8334, 'well plot': 9730, 'world be': 9882, 'be somewhat': 790, 'find br br': 3704, 'br movi just': 1432, 'asia': 476, 'say show': 7810, 'tall': 8814, 'culmin': 2396, 'comprehend': 2187, 'anyth br': 390, 'movi like': 6041, 'much way': 6194, 'anyth br br': 391, 'br br sure': 1300, 'fluff': 3761, 'ticket': 9063, 'interest plot': 4765, 'boll': 1023, 'criticism': 2372, 'assur': 500, 'proof': 7212, 'controversi': 2253, 'numer': 6551, 'filth': 3696, 'trend': 9276, 'hostel': 4535, 'knew': 5126, 'bag': 604, 'cruelti': 2385, 'electr': 2950, 'spree': 8466, 'senseless': 7995, 'yell': 9962, 'just thing': 5028, 'go happen': 4075, 'death row': 2493, 'peopl br': 6825, 'complet lack': 2177, 'movi go': 6024, 'cast crew': 1791, 'just fun': 4980, 'shower': 8145, 'hustler': 4591, 'as long': 463, 'get get': 3964, 'just tri': 5032, 'debra': 2497, 'winger': 9812, 'quaid': 7271, 'flick br': 3747, 'crap br': 2329, 'crap br br': 2330, 'reincarn': 7471, 'br whi': 1547, 'br conclusion': 1340, 'br br whi': 1324, 'br br conclusion': 1156, 'thrown': 9053, 'measure': 5717, 'film movie': 3582, 'rare': 7334, 'shooter': 8102, 'liberti': 5284, 'wait be': 9542, 'voic act': 9523, 'be apart': 670, 'get not': 3987, 'waste': 9600, 'criterion': 2369, 'quirk': 7287, 'br expect': 1364, 'expect br': 3254, 'br second': 1490, 'still br': 8543, 'expect br br': 3255, 'br br second': 1278, 'still br br': 8544, 'peopl see': 6838, 'see horror': 7958, 'think watch': 9028, 'degre': 2529, 'bridget': 1594, 'show charact': 8123, 'charact show': 1899, 'feel not': 3411, 'assembl': 490, 'tragic': 9244, 'car chase': 1742, 'cup tea': 2403, 'mayb not': 5691, 'br cours': 1342, 'prank': 7112, 'realli need': 7395, 'induc': 4689, 'smooth': 8250, 'everywher': 3213, 'poster': 7095, 'not act': 6360, 'movi action': 5958, 'lot movi': 5437, 'movi guy': 6026, 'mostly': 5935, 'love time': 5473, 'be love': 740, 'actor well': 120, 'win award': 9806, 'stori not': 8598, 'love see': 5467, 'pastor': 6781, 'choir': 1970, 'brass': 1568, 'revolt': 7586, 'caricatur': 1760, 'musician': 6224, 'far not': 3360, 'country br': 2298, 'goe back': 4092, 'not spoil': 6482, 'country br br': 2299, 'radar': 7302, 'movi probabl': 6073, 'probabl never': 7172, 'axe': 569, 'still feel': 8546, 'just find': 4979, 'veri scene': 9463, 'well so': 9735, 'not understand': 6499, 'straightforward': 8624, 'princess': 7161, 'just doe': 4971, 'anime': 352, 'mediocre': 5721, 'orient': 6656, 'wizard': 9828, 'heavi metal': 4360, 'music so': 6222, 'not tell': 6489, 'movi take': 6098, 'backward': 596, 'film surpris': 3656, 'phil': 6912, 'matter fact': 5680, 'peac': 6808, 'legendari': 5247, 'shelf': 8079, 'one dimension': 6608, 'immedi': 4638, 'custom': 2414, 'review movi': 7581, 'thing movie': 9000, 'know peopl': 5144, 'peopl so': 6839, 'dvd player': 2883, 'move along': 5952, 'wast film': 9594, 'stoog': 8576, 'opportun see': 6640, 'thing thing': 9009, 'work br': 9863, 'work br br': 9864, 'doo': 2779, 'watch show': 9630, 'just end': 4972, 'whi movi': 9773, 'movi everyon': 6008, 'chuckl': 1998, 'get way': 4002, 'reject': 7473, 'dumber': 2859, 'magician': 5526, 'becaus charact': 841, 'no longer': 6335, 'sit there': 8197, 'oliver': 6594, 'vote br': 9533, 'titl brazil': 9150, 'vote br br': 9534, 'br titl brazil': 1529, 'dandi': 2448, 'meteor': 5757, 'encourag': 2991, 'music scene': 6220, 'year time': 9956, 'even interest': 3139, 'relax': 7477, 'stiller': 8567, 'bless': 990, 'ben stiller': 905, 'watch crap': 9607, 'watch day': 9608, 'like say': 5326, 'just rememb': 5013, 'look just': 5406, 'film place': 3611, 'hidden': 4421, 'spare': 8413, 'imagine': 4635, 'standout': 8491, 'police': 7063, 'br onc': 1452, 'almost never': 245, 'be say': 778, 'br br onc': 1242, 'bloke': 997, 'terri': 8874, 'crocodil': 2374, 'just say': 5016, 'expect be': 3253, 'ban': 615, 'shaw': 8072, 'end up': 3022, 'not whi': 6509, 'money film': 5893, 'still work': 8566, 'realli film': 7387, 'english': 3041, 'position': 7090, 'miniseri': 5813, 'delv': 2542, 'have help': 4293, 'also make': 273, 'someon not': 8359, 'burton': 1667, 'get do': 3957, 'cast not': 1798, 'sort way': 8398, 'work out': 9872, 'havoc': 4333, 'fish': 3723, 'griev': 4149, 'harder': 4246, 'mourn': 5948, 'tragedy': 9243, 'movi doe': 5998, 'monster movi': 5905, 'well charact': 9713, 'there movi': 8961, 'let say': 5271, 'so thing': 8328, 'year still': 9955, 'guy be': 4188, 'be place': 764, 'whi even': 9770, 'world movi': 9888, 'br again': 1092, 'be mayb': 744, 'br br start': 1294, 'place br br': 6968, 'heal': 4345, 'mute': 6229, 'grandfath': 4127, 'alot': 253, 'pace film': 6708, 'pot': 7097, 'plant': 6982, 'save grace': 7793, 'traumat': 9264, 'legaci': 5245, 'crisi': 2365, 'revisit': 7584, 'make interest': 5545, 'movi remind': 6081, 'commit suicide': 2152, 'anybody': 377, 'cinema film': 2006, 'film do': 3502, 'cast member': 1796, 'scene make': 7842, 'be know': 734, 'make mistak': 5552, 'you br': 9983, 'you br br': 9984, 'way back': 9648, 'movi name': 6056, 'movie end': 6136, 'watch origin': 9625, 'voter': 9535, 'minut time': 5826, 'oscar nomin': 6669, 'ancient': 325, 'immort': 4641, 'liner': 5343, 'showcas': 8143, 'puzzl': 7269, 'beauti woman': 830, 'end movie': 3010, 'film becom': 3471, 'perri': 6882, 'randi': 7320, 'film number': 3597, 'time tv': 9127, 'end show': 3017, 'way also': 9647, 'way show': 9673, 'see charact': 7946, 'corni': 2278, 'carey': 1757, 'waitress': 9545, 'mildr': 5788, 'poverti': 7103, 'flirt': 3752, 'shelter': 8082, 'broke': 1611, 'dee': 2515, 'salli': 7758, 'time work': 9133, 'life back': 5292, 'pass time': 6775, 'take back': 8793, 'br later': 1405, 'also love': 272, 'choice': 1969, 'calib': 1701, 'ballet': 613, 'comedi be': 2126, 'br soundtrack': 1504, 'br br soundtrack': 1290, 'wonderful': 9845, 'entir movi': 3078, 'like be': 5321, 'sexuality': 8045, 'way charact': 9652, 'berkeley': 917, 'prophet': 7219, 'time also': 9074, 'coach': 2076, 'jack nicholson': 4830, 'be movi ever': 748, 'elizabeth': 2959, 'drake': 2812, 'mental': 5738, 'asylum': 502, 'vault': 9433, 'antholog': 366, 'keeper': 5073, 'poker': 7059, 'santa claus': 7777, 'season show': 7924, 'charact here': 1885, 'cast br': 1789, 'cast br br': 1790, 'coma': 2112, 'bondag': 1028, 'plot element': 7018, 'movie watch': 6172, 'bradford': 1561, 'banter': 619, 'interfer': 4774, 'go just': 4076, 'effect br': 2929, 'line br': 5337, 'effect br br': 2930, 'line br br': 5338, 'asset': 492, 'effect so': 2933, 'love hate': 5457, 'work so': 9873, 'well stori': 9736, 'act role': 70, 'work so well': 9874, 'br tv': 1533, 'br br tv': 1313, 'whip': 9782, 'download': 2801, 'memoir': 5732, 'miscast': 5836, 'curiosity': 2405, 'life film': 5298, 'end even': 3002, 'recommend movi': 7439, 'einstein': 2942, 'shore': 8106, 'br instead': 1396, 'br course': 1343, 'br br instead': 1202, 'sci': 7869, 'lanc': 5183, 'movi here': 6030, 'resolv': 7536, 'histrion': 4450, 'behind': 884, 'fanat': 3346, 'curti': 2410, 'tide': 9064, 'concoct': 2202, 'repress': 7520, 'detective': 2599, 'luci': 5485, 'mae': 5520, 'qualifi': 7273, 'terrif': 8876, 'crisp': 2367, 'horror thriller': 4529, 'corny': 2279, 'imageri': 4629, 'korda': 5150, 'ralph': 7313, 'richardson': 7601, 'massey': 5659, 'gas': 3911, 'fuel': 3852, 'plagu': 6974, 'glenn': 4053, 'film differ': 3500, 'place film': 6969, 'silver screen': 8166, 'raymond massey': 7359, 'war not': 9578, 'well thing': 9738, 'time still': 9120, 'scienc fiction': 7872, 'sentence': 7999, 'stay away': 8521, 'mani movi': 5612, 'director produc': 2666, 'br movi be': 1430, 'scarface': 7819, 'castro': 1805, 'opportunity': 6641, 'fifti': 3437, 'lopez': 5419, 'cuban': 2393, 'wing': 9811, 'beautifully': 832, 'engross': 3043, 'pfeiffer': 6906, 'murray': 6208, 'omar': 6598, 'peckinpah': 6814, 'al pacino': 205, 'man name': 5596, 'get there': 3995, 'well role': 9731, 'rather film': 7347, 'be end': 703, 'whatsoever': 9760, 'peer': 6817, 'genet': 3928, 'disappear': 2677, 'busey': 1670, 'science': 7874, 'period time': 6879, 'onli thing': 6627, 'thing life': 8994, 'action film': 87, 'make lot': 5548, 'spin': 8440, 'movie charact': 6134, 'film making': 3571, 'film know': 3556, 'dinosaur': 2646, 'lab': 5167, 'blob': 993, 'meredith': 5744, 'plot hole': 7021, 'here thing': 4408, 'guy so': 4195, 'far away': 3352, 'movie thing': 6168, 'br guess': 1384, 'see becaus': 7943, 'br br guess': 1193, 'packag': 6713, 'barbra': 624, 'feminist': 3423, 'descent': 2573, 'bud': 1634, 'esther': 3109, 'poignant': 7044, 'dynam': 2890, 'resent': 7530, 'kristofferson': 5155, 'incorpor': 4674, 'rock star': 7657, 'break br': 1576, 'give break': 4033, 'close up': 2060, 'break br br': 1577, 'then thing': 8942, 'invest': 4791, 'mathieu': 5675, 'signal': 8158, 'soon br': 8383, 'line be': 5336, 'soon br br': 8384, 'deriv': 2570, 'ranger': 7326, 'thing happen': 8991, 'version not': 9475, 'power ranger': 7109, 'france': 3814, 'recov': 7444, 'wwi': 9928, 'smug': 8251, 'massacre': 5658, 'rumor': 7725, 'life as': 5291, 'br life': 1408, 'then year': 8947, 'together br': 9164, 'have heart': 4292, 'br br life': 1211, 'domin': 2771, 'one lin': 6614, 'automat': 544, 'blunt': 1008, 'arquett': 440, 'inabl': 4661, 'misguid': 5844, 'campus': 1717, 'kid br': 5091, 'be actor': 662, 'not tri': 6497, 'be believ': 677, 'watch scene': 9628, 'proud': 7228, 'actor ever': 104, 'list goe': 5351, 'lump': 5495, 'clint': 2051, 'leon': 5255, 'prospect': 7222, 'wild': 9799, 'disord': 2702, 'buddy': 1636, 'justic': 5044, 'dust': 2873, 'mice': 5767, 'not one': 6452, 'perform ever': 6863, 'mormon': 5927, 'spectacl': 8421, 'denis': 2551, 'almost scene': 246, 'movi differ': 5994, 'creep': 2355, 'emma': 2977, 'ellen': 2960, 'basic': 642, 'tri kill': 9286, 'way movie': 9666, 'jesus': 4883, 'film shot': 3638, 'give br': 4031, 'give br br': 4032, 'show watch': 8141, 'down earth': 2794, 'wine': 9810, 'br theme': 1520, 'redempt': 7450, 'simple': 8170, 'compassion': 2165, 'love be': 5453, 'peopl br br': 6826, 'hello': 4372, 'buster': 1676, 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'blais': 980, 'alice': 219, 'pinjar': 6952, 'depalma': 2557, 'palermo': 6725, 'hackenstein': 4201}

-------------------------

CountVectorizer

/usr/local/lib/python3.7/dist-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function get_feature_names is deprecated; get_feature_names is deprecated in 1.0 and will be removed in 1.2. Please use get_feature_names_out instead.
  warnings.warn(msg, category=FutureWarning)

[[0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]
 ...
 [0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]]

-------------------------

TF-IDF
[6.25919665 7.72553372 7.07494615 ... 7.43785164 7.90785527 7.90785527]
10000

-------------------------

Predictions
[1 0 0 ... 0 0 0]


---- Classification report ----
              precision    recall  f1-score   support

     positif       0.58      0.97      0.73      1267
     negatif       0.89      0.29      0.44      1233

    accuracy                           0.63      2500
   macro avg       0.74      0.63      0.58      2500
weighted avg       0.74      0.63      0.58      2500

Discussion des résultats

Sans grande surprise les performances baissent lorsque l'on appriche la fonction pos_tag_filter en ne gardant uniquement que les mots associés aux tags acceptés, la phrase perd de son sens. De plus, la phrase n'est plus bien construire.

Fine-tuning d'un modèle Bert

Suivant le modèle du TP précédent, fine-tunez le modèle Bert le plus léger disponible sur les données d'IMDB et comparez avec les résultats obtenus précédemment. Encore une fois, si possible, réalisez cette étude pour des quantités de données différentes.

Check if the GPU is available

import torch

if torch.cuda.is_available():       
    device = torch.device("cuda")
    print(f'There are {torch.cuda.device_count()} GPU(s) available.')
    print('Device name:', torch.cuda.get_device_name(0))

else:
    print('No GPU available, using the CPU instead.')
    device = torch.device("cpu")

There are 1 GPU(s) available.
Device name: Tesla T4

Installation the dependences

from transformers import DistilBertTokenizerFast, DistilBertModel, DistilBertForSequenceClassification
from transformers import Trainer, TrainingArguments

import pprint
pp = pprint.PrettyPrinter(indent=4)

Encoding data with DistilBERT

1. Le texte doit être tronqué s'il est supérieur à 256/512 tokens ou paddé s'il est inférieur à 256 ou 512 tokens (selon la taille du modèle). Les mots peuvent également devoir être séparés en sous-mots : Les modèles de type BERT utilisent des tokenizers différents, construits pour gérer un vocabulaire de taille fixe. Tout mot qui n'est pas dans le vocabulaire est divisé en sous-mots qui le sont. Le tokenizer de BERT est basé sur Wordpiece.

2. BERT utilise des jetons spéciaux, qui seront ajoutés :

   • [CLS] - Jeton de début de chaque document.
   • [SEP] - Séparateur entre chaque phrase.
   • [PAD] - Remplissage à la fin du document autant de fois que nécessaire, jusqu'à 256/512 jetons.
   • ## - Indique le début d'un sous-mot, ou "morceau de mot".

Nous utiliserons le modèle DistilBERT pour gagner de la place (puisqu'il s'agit d'une version distillée du modèle BERT complet), et nous utiliserons la version sans casse. Nous devons faire attention à utiliser le tokenizer correspondant.

tokenizer = DistilBertTokenizerFast.from_pretrained('distilbert-base-uncased')

Encoding training and testing data

train_texts_input = tokenizer([sentence for sentence in train_texts_splt],
                         truncation=True,
                         padding='max_length', 
                         return_tensors="pt")

test_texts_input = tokenizer([sentence for sentence in val_texts],
                              truncation=True,
                              padding='max_length', 
                              return_tensors="pt")

Regardons le résultat de l'encodage du dataset d'entrainement

Pour ce nous allons prendre comme exemple la première phrase de notre dataset que l'on peut considéré comme un document

Résultat de l'encoding train_texts_input

print("----- train_texts_input -----")

print("Original sentence")
print(train_texts_splt[0])

print("\n\nTokens")
pp.pprint(train_texts_input[0].tokens)

print("\n\nSpecial Tokens")
pp.pprint(train_texts_input[0].special_tokens_mask)

# The number of tokens is not the same anymore
print("\n\nText length")
pp.pprint(len(train_texts_splt[0]))

print("\n\nText tokenized length")
pp.pprint(len(train_texts_input[0].tokens))

----- train_texts_input -----
Original sentence
I bought this from Blockbuster for 99p. The guy behind the counter said the reason it was so cheap was because the disc was scratched to sh*t, but failed to mention that the reason it was so cheap was because the film was a p*ss poor effort that sucked harder than Paris Hilton in a hotel room home video. Talking of home videos, since when has it been fair game to release them as films - I mean to say, films used to employ actors and technicians and scriptwriters and so on - not any more - just gather your friends and lame-o ideas together for the weekend, lavish the production with an £8.00 budget, and get someone to fall down the stairs with a Casio keyboard (the soundtrack) - then slap it on the shelves, for some poor sap (me), to take home in lonely desperation. But here's the clincher - I fast forwarded through most of this, and tossed it to one side, ready for the hammers... until the next night, while watching a Darren Day horror 'Hellbreed' (£1.99 to take home and keep from a different Blockbuster). Now this film made 'Grim Weekend' look like The Exorcist, so I slapped Grim Weekend back on, to catch up on some of the moments listed on the wonderful IMDb boards, that viewers claimed were hilarious. Sure enough, once I had got over the misery, the pain, and the horror, of realising Grim Weekend was utter chod on toast, I could enjoy, savour, and downright get down to the funny stuff. And there's a lot of it. Check the boards. Then check the flick. Hell, it might even be worth it. AWWWWW CRAP!


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Text length
1522


Text tokenized length
512

Résultat de l'encoding de test_texts_input

print("----- test_texts_input -----")

print("Original sentence")
print(val_texts[0])

print("\n\nTokens")
pp.pprint(test_texts_input[0].tokens)

print("\n\nSpecial Tokens")
pp.pprint(test_texts_input[0].special_tokens_mask)

# The number of tokens is not the same anymore
print("\n\nText length")
pp.pprint(len(val_texts[0]))

print("\n\nText tokenized length")
pp.pprint(len(test_texts_input[0].tokens))

----- test_texts_input -----
Original sentence
The Twilight Zone has achieved a certain mythology about it--much like Star Trek. That's because there are many devoted lovers of the show that no matter what think every episode was a winner. They are the ones who score each individual show a 10 and cannot objectively evaluate the show. Because of this, a while back I reviewed all the original Star Trek episodes (the good and the bad) because the overall ratings and reviews were just too positive. Now, it's time to do the same for The Twilight Zone.<br /><br />While I have scored many episodes 10, this one gets a 3 simply because it was bad. The writing was in fact embarrassingly bad. Two people from opposing sides in a great war are seen wandering about through the entire episode. After a while, it's apparent that they are the only two people left on Earth--as you learn in the really stupid and totally unconvincing conclusion. Usually the twist at the end makes the episode great--this one killed it!


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Text length
965


Text tokenized length
512

On peut remarquer que l'encodage du premier document (i.e premier texte) est composé à la fin d'une séquence du token [PAD]. Cela s'exeplique par le fait que la longueur de la séquence n'est pas assez grand pour tenir sur un séquence de dmiension 512. Ainsi la fin de l'encodage de la fin de la séquence est remplie par le token [PAD] pour respecter une séquence de 512

Création de la classe Torch

Nous devons créer une classe Torch personnalisée pour transformer les encodages en entrées du modèle, pour deux raisons principales :

• Ajouter les étiquettes à l'objet d'encodage, puisque cela est nécessaire pour affiner un modèle de classification.
• Fournir une interface pour le modèle pour faire des mini-batchs à partir des encodages.

import torch

class FineTuningDataset(torch.utils.data.Dataset):
    def __init__(self, encodings, labels):
        self.encodings = encodings
        self.labels = labels

    def __getitem__(self, idx):
        item = {key: torch.tensor(val[idx]) for key, val in self.encodings.items()}
        item['labels'] = torch.tensor(self.labels[idx])
        return item

    def __len__(self):
        return len(self.labels)

train_texts_dataset = FineTuningDataset(train_texts_input, train_labels_splt)
test_texts_dataset = FineTuningDataset(test_texts_input, val_labels)

Load the model and pass to CUDA

bert_clf_model = DistilBertForSequenceClassification.from_pretrained('distilbert-base-uncased', num_labels= max(train_labels_splt) + 1).to("cuda")

Some weights of the model checkpoint at distilbert-base-uncased were not used when initializing DistilBertForSequenceClassification: ['vocab_projector.bias', 'vocab_transform.bias', 'vocab_projector.weight', 'vocab_layer_norm.weight', 'vocab_transform.weight', 'vocab_layer_norm.bias']
- This IS expected if you are initializing DistilBertForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing DistilBertForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
Some weights of DistilBertForSequenceClassification were not initialized from the model checkpoint at distilbert-base-uncased and are newly initialized: ['classifier.weight', 'pre_classifier.weight', 'classifier.bias', 'pre_classifier.bias']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.

On défini la métrique d'évaluation

from sklearn.metrics import accuracy_score

def compute_metrics(pred):
  labels = pred.label_ids
  preds = pred.predictions.argmax(-1)
  acc = accuracy_score(labels, preds)

  return {
      'accuracy': acc,
  }

On défni les argument de l'entrainement

training_args = TrainingArguments(
    num_train_epochs=3,              # total number of training epochs
    per_device_train_batch_size=16,  # batch size per device during training
    per_device_eval_batch_size=20,   # batch size for evaluation
    learning_rate=5e-5,              # initial learning rate for Adam optimizer
    warmup_steps=100,                # number of warmup steps for learning rate scheduler (set lower because of small dataset size)
    weight_decay=0.01,               # strength of weight decay
    output_dir='./results',          # output directory
    logging_dir='./logs',            # directory for storing logs
    logging_steps=100,               # number of steps to output logging (set lower because of small dataset size)
    evaluation_strategy='steps',     # evaluate during fine-tuning so that we can see progress
)

bert_trainer = Trainer(
    model=bert_clf_model,                      
    args=training_args,                  
    train_dataset=train_texts_dataset,         
    eval_dataset=test_texts_dataset,           
    compute_metrics=compute_metrics       
)

On entraine le modèle BERT

bert_trainer.train()

/usr/local/lib/python3.7/dist-packages/transformers/optimization.py:310: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning
  FutureWarning,
***** Running training *****
  Num examples = 10000
  Num Epochs = 3
  Instantaneous batch size per device = 16
  Total train batch size (w. parallel, distributed & accumulation) = 16
  Gradient Accumulation steps = 1
  Total optimization steps = 1875
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  if __name__ == '__main__':

[1875/1875 38:50, Epoch 3/3]

Step	Training Loss	Validation Loss	Accuracy
100	0.565700	0.370032	0.834800
200	0.315900	0.283250	0.882800
300	0.302500	0.315860	0.884800
400	0.300300	0.350490	0.880000
500	0.299200	0.244296	0.904800
600	0.249600	0.292711	0.887600
700	0.181500	0.304129	0.906400
800	0.167000	0.392374	0.890000
900	0.159700	0.338305	0.904800
1000	0.154800	0.308881	0.910400
1100	0.136000	0.356924	0.903600
1200	0.171200	0.292335	0.909600
1300	0.113800	0.356132	0.912000
1400	0.052700	0.425024	0.906800
1500	0.057100	0.412860	0.912000
1600	0.099300	0.371894	0.912400
1700	0.067600	0.395746	0.910800
1800	0.060300	0.394630	0.910000

***** Running Evaluation *****
  Num examples = 2500
  Batch size = 20
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  if __name__ == '__main__':
***** Running Evaluation *****
  Num examples = 2500
  Batch size = 20
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  if __name__ == '__main__':
***** Running Evaluation *****
  Num examples = 2500
  Batch size = 20
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  if __name__ == '__main__':
***** Running Evaluation *****
  Num examples = 2500
  Batch size = 20
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  if __name__ == '__main__':
***** Running Evaluation *****
  Num examples = 2500
  Batch size = 20
Saving model checkpoint to ./results/checkpoint-500
Configuration saved in ./results/checkpoint-500/config.json
Model weights saved in ./results/checkpoint-500/pytorch_model.bin
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  if __name__ == '__main__':
***** Running Evaluation *****
  Num examples = 2500
  Batch size = 20
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  if __name__ == '__main__':
***** Running Evaluation *****
  Num examples = 2500
  Batch size = 20
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  if __name__ == '__main__':
***** Running Evaluation *****
  Num examples = 2500
  Batch size = 20
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  if __name__ == '__main__':
***** Running Evaluation *****
  Num examples = 2500
  Batch size = 20
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  if __name__ == '__main__':
***** Running Evaluation *****
  Num examples = 2500
  Batch size = 20
Saving model checkpoint to ./results/checkpoint-1000
Configuration saved in ./results/checkpoint-1000/config.json
Model weights saved in ./results/checkpoint-1000/pytorch_model.bin
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  if __name__ == '__main__':
***** Running Evaluation *****
  Num examples = 2500
  Batch size = 20
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  if __name__ == '__main__':
***** Running Evaluation *****
  Num examples = 2500
  Batch size = 20
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  if __name__ == '__main__':
***** Running Evaluation *****
  Num examples = 2500
  Batch size = 20
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  if __name__ == '__main__':
***** Running Evaluation *****
  Num examples = 2500
  Batch size = 20
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  if __name__ == '__main__':
***** Running Evaluation *****
  Num examples = 2500
  Batch size = 20
Saving model checkpoint to ./results/checkpoint-1500
Configuration saved in ./results/checkpoint-1500/config.json
Model weights saved in ./results/checkpoint-1500/pytorch_model.bin
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  if __name__ == '__main__':
***** Running Evaluation *****
  Num examples = 2500
  Batch size = 20
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  if __name__ == '__main__':
***** Running Evaluation *****
  Num examples = 2500
  Batch size = 20
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  if __name__ == '__main__':
***** Running Evaluation *****
  Num examples = 2500
  Batch size = 20
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  if __name__ == '__main__':


Training completed. Do not forget to share your model on huggingface.co/models =)

TrainOutput(global_step=1875, training_loss=0.1859624917348226, metrics={'train_runtime': 2331.4005, 'train_samples_per_second': 12.868, 'train_steps_per_second': 0.804, 'total_flos': 3974021959680000.0, 'train_loss': 0.1859624917348226, 'epoch': 3.0})

On évalue le modèle

bert_trainer.evaluate()

***** Running Evaluation *****
  Num examples = 2500
  Batch size = 20
/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
  if __name__ == '__main__':

[125/125 00:45]

{'epoch': 3.0,
 'eval_accuracy': 0.9124,
 'eval_loss': 0.39310315251350403,
 'eval_runtime': 46.3073,
 'eval_samples_per_second': 53.987,
 'eval_steps_per_second': 2.699}

Synthèse et discussion des résultats

Modèle	Accuracy
{CountVertorizer + MultinomialNB}	0.86
{CountVertorizer + TF-IDF + MultinomialNB}	0.87
Stemming + {CountVertorizer + TF-IDF + MultinomialNB}	0.84
Stemming + Pos Tag Filter + {CountVertorizer + TF-IDF + MultinomialNB}	0.63
{DistilBERT}	0.912

En effet, le modèle {CountVertorizer + MultinomialNB} obtient des résultats très différent en fonction des hyperparamètres choisis pour CountVectorizer. Toutefois, grâce au fait que nous avons "fine-tuné" les hyperparamètres du modèle nous avons été en mesure de trouver la meilleure combinaison des hyperparamètres qui maximise la métrique de l'accuracy.

En utilisant les mêmes hyperparamètres du CountVertorizer du modèle précédent pour le modèle {CountVertorizer + TF-IDF + MultinomialNB}, nous avons obtenu une meilleure accuracy. En y ajoutant un modèle TF-IDF nous avons réussi à améliorer les représentations du `BoW.

Toutefois, sans grande surprise, on constate que le modèle BERT surclasse les autres modèles de classification.